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• 1.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Anaesthesiology and Intensive Care.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology. Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology. Karolinska Inst, Dept Neurosci, Stockholm, Sweden. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Anaesthesiology and Intensive Care. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Orthopaedics. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology. Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Family Medicine and Preventive Medicine.
Visualization of painful inflammation in patients with pain after traumatic ankle sprain using [(11)C]-D-deprenyl PET/CT.2017In: Scandinavian Journal of Pain, ISSN 1877-8860, E-ISSN 1877-8879, Vol. 17, p. 418-424Article in journal (Refereed)

BACKGROUND AND AIMS: Positron emission tomography (PET) with the radioligand [(11)C]-D-deprenyl has shown increased signal at location of pain in patients with rheumatoid arthritis and chronic whiplash injury. The binding site of [(11)C]-D-deprenyl in peripheral tissues is suggested to be mitochondrial monoamine oxidase in cells engaged in post-traumatic inflammation and tissue repair processes. The association between [(11)C]-D-deprenyl uptake and the transition from acute to chronic pain remain unknown. Further imaging studies of musculoskeletal pain at the molecular level would benefit from establishing a clinical model in a common and well-defined injury in otherwise healthy and drug-naïve subjects. The aim of this study was to investigate if [(11)C]-D-deprenyl uptake would be acutely elevated in unilateral ankle sprain and if tracer uptake would be reduced as a function of healing, and correlated with pain localizations and pain experience.

METHODS: Eight otherwise healthy patients with unilateral ankle sprain were recruited at the emergency department. All underwent [(11)C]-D-deprenyl PET/CT in the acute phase, at one month and 6-14 months after injury.

RESULTS: Acute [(11)C]-D-deprenyl uptake at the injury site was a factor of 10.7 (range 2.9-37.3) higher than the intact ankle. During healing, [(11)C]-D-deprenyl uptake decreased, but did not normalize until after 11 months. Patients experiencing persistent pain had prolonged [(11)C]-D-deprenyl uptake in painful locations.

CONCLUSIONS AND IMPLICATIONS: The data provide further support that [(11)C]-D-deprenyl PET can visualize, quantify and follow processes in peripheral tissue that may relate to soft tissue injuries, inflammation and associated nociceptive signaling. Such an objective correlate would represent a progress in pain research, as well as in clinical pain diagnostics and management.

• 2.
Imperial College, London.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Biases of correlograms and of AR representations of stationary series2012In: Journal of Time Series Econometrics, ISSN 1941-1928, E-ISSN 1941-1928, Vol. 4, no 1Article in journal (Refereed)

We derive the relation between the biases of correlograms and of estimates of auto-regressive AR(k) representations of stationary series, and we illustrate it with a simple AR example. The new relation allows for k to vary with the sample size, which is a representation that can be used for most stationary processes. As a result, the biases of the estimators of such processes can now be quantified explicitly and in a unified way.

• 3. Adami, Johanna
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Oncology, Radiology and Clinical Immunology.
Smoking and the risk of leukemia, lymphoma, and multiple myeloma (Sweden)1998In: Cancer Causes and Control, ISSN 0957-5243, E-ISSN 1573-7225, Vol. 9, no 1, p. 49-56Article in journal (Refereed)

While several epidemiologic studies have indicated a link between smoking and the risk of developing hematolymphoproliferative cancers (chiefly leukemias, lymphomas, and multiple myelomas), in particular myeloid leukemia, the role of tobacco in the etiology of these neoplasms remains unclear. To evaluate the potential impact of tobacco use on development of leukemia, lymphoma, and multiple myeloma, we conducted a cohort study of 334,957 Swedish construction workers using prospectively collected exposure-information with complete long-term follow-up. A total of 1,322 incident neoplasms occurred during the study period, 1971-91. We found no significant association between smoking status, number of cigarettes smoked, or duration of smoking and the risk of developing leukemias, lymphomas, or multiple myeloma. There was a suggestion of a positive association between smoking and the risk of developing Hodgkin's disease, although the rate ratios were not significantly elevated, except for young current smokers. No positive dose-risk trends emerged. Our study provides no evidence that smoking bears any major relationship to the occurrence of leukemias, non-Hodgkin's lymphomas, or multiple myeloma.

• 4.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Forecasting GDP Growth, or How Can Random Forests Improve Predictions in Economics?2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis

GDP is used to measure the economic state of a country and accurate forecasts of it is therefore important. Using the Economic Tendency Survey we investigate forecasting quarterly GDP growth using the data mining technique Random Forest. Comparisons are made with a benchmark AR(1) and an ad hoc linear model built on the most important variables suggested by the Random Forest. Evaluation by forecasting shows that the Random Forest makes the most accurate forecast supporting the theory that there are benefits to using Random Forests on economic time series.

• 5.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
A homogeneity test of large dimensional covariance matrices under non-normality2018In: Kybernetika (Praha), ISSN 0023-5954, E-ISSN 1805-949X, Vol. 54, no 5, p. 908-920Article in journal (Refereed)

A test statistic for homogeneity of two or more covariance matrices is presented when the distributions may be non-normal and the dimension may exceed the sample size. Using the Frobenius norm of the difference of null and alternative hypotheses, the statistic is constructed as a linear combination of consistent, location-invariant, estimators of trace functions that constitute the norm. These estimators are defined as U-statistics and the corresponding theory is exploited to derive the normal limit of the statistic under a few mild assumptions as both sample size and dimension grow large. Simulations are used to assess the accuracy of the statistic.

• 6.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
A significance test of the RV coefficient in high dimensions2019In: Computational Statistics & Data Analysis, ISSN 0167-9473, E-ISSN 1872-7352, Vol. 131, p. 116-130Article in journal (Refereed)

The RV coefficient is an important measure of linear dependence between two multivariate data vectors. Using unbiased and computationally efficient estimators of its components, a modification to the RV coefficient is proposed, and used to construct a test of significance for the true coefficient. The modified estimator improves the accuracy of the original and, along with the test, can be applied to data with arbitrarily large dimensions, possibly exceeding the sample size, and the underlying distribution need only have finite fourth moment. Exact and asymptotic properties are studied under fairly general conditions. The accuracy of the modified estimator and the test is shown through simulations under a variety of parameter settings. In comparisons against several existing methods, both the proposed estimator and the test exhibit similar performance to the distance correlation. Several real data applications are also provided.

• 7.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
A unified approach to testing mean vectors with large dimensions2018In: AStA Advances in Statistical Analysis, ISSN 1863-8171, E-ISSN 1863-818XArticle in journal (Refereed)
• 8.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
A U-statistic approach for a high-dimensional two-sample mean testing problem under non-normality and Behrens-Fisher setting2014In: Annals of the Institute of Statistical Mathematics, ISSN 0020-3157, E-ISSN 1572-9052, Vol. 66, no 1, p. 33-61Article in journal (Refereed)

A two-sample test statistic is presented for testing the equality of mean vectors when the dimension, , exceeds the sample sizes, , and the distributions are not necessarily normal. Under mild assumptions on the traces of the covariance matrices, the statistic is shown to be asymptotically Chi-square distributed when . However, the validity of the test statistic when is fixed but large, including , and when the distributions are multivariate normal, is shown as special cases. This two-sample Chi-square approximation helps us establish the validity of Box's approximation for high-dimensional and non-normal data to a two-sample setup, valid even under Behrens-Fisher setting. The limiting Chi-square distribution of the statistic is obtained using the asymptotic theory of degenerate -statistics, and using a result from classical asymptotic theory, it is further extended to an approximate normal distribution. Both independent and paired-sample cases are considered.

• 9.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Generalized tests of correlation for vectors with large dimensions using modified RV coefficient2019Report (Other academic)

Tests of zero correlation between two or more vectors with large dimension, possibly largerthan the sample size, are considered when the data may not necessarily follow a normal distribution. A single sample case for several vectors is rst proposed, which is then extended tothe common covariance matrix under the assumption of homogeneity across several independentpopulations. The test statistics are constructed using a recently proposed modicationof the RV coecient for high-dimensional vectors. The accuracy of the tests is shown through simulations.

• 10.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Location-invariant and non-invariant tests for large dimensional covariance matrices under normality and non-normality2014Report (Other academic)

Test statistics for homogeneity, sphericity and identity of high-dimensional covariance matrices are presented under a wide variety of very general conditions when the dimension of the vector, \$p\$, may exceed the sample size, \$n_i\$, \$i = 1, \ldots, g\$. First, location-invariant tests are presented under normality assumption, followed by their robustness to normality by replacing the normality assumption with a mild alternative multivariate model. The two types of tests are then presented in non-invariant form, again under normality and non-normality. Tests of homogeneity of covariance matrices in all cases are immediately supplemented by the tests for sphericity and identity of the common covariance matrix under the null hypothesis. Both location-invariant and non-invariant tests are composed of estimators that are defined as \$U\$-statistics with kernels of different degrees. Hence, the asymptotic theory of \$U\$-statistics is employed to arrive at the limiting null and alternative distributions of tests for all cases. These limit distributions are derived using a very mild and practically viable set of assumptions mainly on the traces of the unknown covariance matrices. Finally, corrections and improvements of a few other tests are also presented.

• 11.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Location-invariant Multi-sample U-tests for Covariance Matrices with Large Dimension2017In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 44, no 2, p. 500-523Article in journal (Refereed)

For two or more multivariate distributions with common covariance matrix, test statistics for certain special structures of the common covariance matrix are presented when the dimension of the multivariate vectors may exceed the number of such vectors. The test statistics are constructed as functions of location-invariant estimators defined as U-statistics, and the corresponding asymptotic theory is used to derive the limiting distributions of the proposed tests. The properties of the test statistics are established under mild and practical assumptions, and the same are numerically demonstrated using simulation results with small or moderate sample sizes and large dimensions.

• 12.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Location-invariant tests of homogeneity of large-dimensional covariance matrices2017In: Journal of Statistical Theory and Practice, ISSN 1559-8608, E-ISSN 1559-8616, Vol. 11, no 4, p. 731-745Article in journal (Refereed)

A test statistic for homogeneity of two or more covariance matrices of large dimensions is presented when the data are multivariate normal. The statistic is location-invariant and defined as a function of U-statistics of non-degenerate kernels so that the corresponding asymptotic theory is employed to derive the limiting normal distribution of the test under a few mild and practical assumptions. Accuracy of the test is shown through simulations with different parameter settings.

• 13.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Multiple comparisons of mean vectors with large dimension under general conditions2019In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163Article in journal (Refereed)

Multiple comparisons for two or more mean vectors are considered when the dimension of the vectors may exceed the sample size, the design may be unbalanced, populations need not be normal, and the true covariance matrices may be unequal. Pairwise comparisons, including comparisons with a control, and their linear combinations are considered. Under fairly general conditions, the asymptotic multivariate distribution of the vector of test statistics is derived whose quantiles can be used in multiple testing. Simulations are used to show the accuracy of the tests. Real data applications are also demonstrated.

• 14.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Testing homogeneity of several covariance matrices and multi-sample sphericity for high-dimensional data under non-normality2017In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 46, no 8, p. 3738-3753Article in journal (Refereed)

A test for homogeneity of g 2 covariance matrices is presented when the dimension, p, may exceed the sample size, n(i), i = 1, ..., g, and the populations may not be normal. Under some mild assumptions on covariance matrices, the asymptotic distribution of the test is shown to be normal when n(i), p . Under the null hypothesis, the test is extended for common covariance matrix to be of a specified structure, including sphericity. Theory of U-statistics is employed in constructing the tests and deriving their limits. Simulations are used to show the accuracy of tests.

• 15.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Tests for independence of vectors with large dimension2017Report (Other academic)

Given a random sample of n iid vectors, each of dimension p and partitioned into b sub- vectors of sizes pi, i = 1;:::;b. Location-invariant and non-invariant test statistics for independence of sub-vectors are presented when pi may exceed n and the distribution need not be normal. The tests are composed of U -statistics based estimators of the Frobenius norm of the di erence between the null and alternative hypotheses. Asymptotic distributions of the tests are provided for n;pi! 1, where their nite-sample performance is demonstrated through simulations. Some related and subsequent tests are brie y described. Relations of the proposed tests to certain multivariate measures are discussed, which are of interest on their own.

• 16.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
KTH, Stockholm, Sweden.
A U-classifier for high-dimensional data under non-normality2018In: Journal of Multivariate Analysis, ISSN 0047-259X, E-ISSN 1095-7243, Vol. 167, p. 269-283Article in journal (Refereed)

A classifier for two or more samples is proposed when the data are high-dimensional and the distributions may be non-normal. The classifier is constructed as a linear combination of two easily computable and interpretable components, the U-component and the P-component. The U-component is a linear combination of U-statistics of bilinear forms of pairwise distinct vectors from independent samples. The P-component, the discriminant score, is a function of the projection of the U-component on the observation to be classified. Together, the two components constitute an inherently bias-adjusted classifier valid for high-dimensional data. The classifier is linear but its linearity does not rest on the assumption of homoscedasticity. Properties of the classifier and its normal limit are given under mild conditions. Misclassification errors and asymptotic properties of their empirical counterparts are discussed. Simulation results are used to show the accuracy of the proposed classifier for small or moderate sample sizes and large dimensions. Applications involving real data sets are also included.

• 17.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Tests for high-dimensional covariance matrices using the theory of U-statistics2015In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 85, no 13, p. 2619-2631Article in journal (Refereed)

Test statistics for sphericity and identity of the covariance matrix are presented, when the data are multivariate normal and the dimension, p, can exceed the sample size, n. Under certain mild conditions mainly on the traces of the unknown covariance matrix, and using the asymptotic theory of U-statistics, the test statistics are shown to follow an approximate normal distribution for large p, also when p >> n. The accuracy of the statistics is shown through simulation results, particularly emphasizing the case when p can be much larger than n. A real data set is used to illustrate the application of the proposed test statistics.

• 18.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Tests of Covariance Matrices for High Dimensional Multivariate Data Under Non Normality2015In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 44, no 7, p. 1387-1398Article in journal (Refereed)

Ahmad et al. (in press) presented test statistics for sphericity and identity of the covariance matrix of a multivariate normal distribution when the dimension, p, exceeds the sample size, n. In this note, we show that their statistics are robust to normality assumption, when normality is replaced with certain mild assumptions on the traces of the covariance matrix. Under such assumptions, the test statistics are shown to follow the same asymptotic normal distribution as under normality for large p, also whenp >> n. The asymptotic normality is proved using the theory of U-statistics, and is based on very general conditions, particularly avoiding any relationship between n and p.

• 19.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
A note on mean testing for high dimensional multivariate data under non-normality2013In: Statistica neerlandica (Print), ISSN 0039-0402, E-ISSN 1467-9574, Vol. 67, no 1, p. 81-99Article in journal (Refereed)

A test statistic is considered for testing a hypothesis for the mean vector for multivariate data, when the dimension of the vector, p, may exceed the number of vectors, n, and the underlying distribution need not necessarily be normal. With n,p?8, and under mild assumptions, but without assuming any relationship between n and p, the statistic is shown to asymptotically follow a chi-square distribution. A by product of the paper is the approximate distribution of a quadratic form, based on the reformulation of the well-known Box's approximation, under high-dimensional set up. Using a classical limit theorem, the approximation is further extended to an asymptotic normal limit under the same high dimensional set up. The simulation results, generated under different parameter settings, are used to show the accuracy of the approximation for moderate n and large p.

• 20.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Testing homogeneity of several covariance matrices and multi-sample sphericity for high-dimensional data2013Report (Other academic)

A test statistic for testing homogeneity of g 2 covariance matri-ces is presented when the data are assumed multivariate normal and thedimension of the vector, p, may exceed the number of such vectors, ni,i = 1; : : : ; g. U-statistics based unbiased and location-invariant estima-tors are used to dene the test statistic. Further, using the asymptotictheory of U-statistics, the test statistic is shown to follow an approximatenormal distribution. This limiting distribution is based on certain mildassumptions on the traces of the unknown common population covariancematrix. Under the null hypothesis of homogeneity of covariance matrices,the test statistic is further extended to test multi-sample sphericity andidentity of the common covariance matrix.

• 21.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Some tests for high-dimensional one-way MANOVA and related hypotheses under non-normality and heteroscedasticity2014Report (Other academic)

A test statistic for the equality of g 2 mean vectors, with particularemphasis on the MANOVA case for g 3, is derived when the dimensionp of the vectors may exceed the number of such vectors, ni, i = 1; : : : ; g.The asymptotic distribution of the test statistic, composed of linear com-binations of one- and two-sample U-statistics with degenerate bivariatekernels, is derived under fairly general conditions. In particular, the g pop-ulations do not need to be necessarily normal and may also have unequalcovariance matrices. Under certain mild assumptions on the moments ofthe eigenvalues of unknown covariance matrices, the limit distribution ofthe test statistic is shown to follow a 2 distribution, further extended tonormal limit, as ni; p ! 1. The statistic is further extended for testingany general linear hypothesis, taking prole analysis as one of the mostcommonly used cases. Extensive simulation results are used to show theaccuracy of the test statistic for both test size and power. Practical useof the test statistics is also demonstrated using real data examples.

• 22.
Lund Univ, Div Resp Med & Allergol, Dept Clin Sci, Lund, Sweden.
Univ Orebro, Sch Med Sci, Dept Resp Med, Orebro, Sweden. Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics. Lund Univ, Div Resp Med & Allergol, Dept Clin Sci, Lund, Sweden.
Long-Term Oxygen Therapy 24 vs 15 h/day and Mortality in Chronic Obstructive Pulmonary Disease2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 9, article id e0163293Article in journal (Refereed)

Long-term oxygen therapy (LTOT) >= 15 h/day improves survival in hypoxemic chronic obstructive pulmonary disease ( COPD). LTOT 24 h/day is often recommended but may pose an unnecessary burden with no clear survival benefit compared with LTOT 15 h/day. The aim was to test the hypothesis that LTOT 24 h/day decreases all-cause, respiratory, and cardiovascular mortality compared to LTOT 15 h/day in hypoxemic COPD. This was a prospective, observational, population-based study of COPD patients starting LTOT between October 1, 2005 and June 30, 2009 in Sweden. Overall and cause-specific mortality was analyzed using Cox and Fine-Gray regression, controlling for age, sex, prescribed oxygen dose, PaO2 (air), PaCO2 (air), Forced Expiratory Volume in one second (FEV1), WHO performance status, body mass index, comorbidity, and oral glucocorticoids. A total of 2,249 included patients were included with a median follow-up of 1.1 years (interquartile range, 0.6-2.1). 1,129 (50%) patients died and no patient was lost to follow-up. Higher LTOT duration analyzed as a continuous variable was not associated with any change in mortality rate (hazard ratio [HR] 1.00; (95% confidence interval [CI], 0.98 to 1.02) per 1 h/day increase above 15 h/day. LTOT exactly 24 h/day was prescribed in 539 (24%) patients and LTOT 15-16 h/day in 1,231 (55%) patients. Mortality was similar between the groups for all-cause, respiratory and cardiovascular mortality. In hypoxemic COPD, LTOT 24 h/day was not associated with a survival benefit compared with treatment 15-16 h/day. A design for a registry-based randomized trial (R-RCT) is proposed.

• 23.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Forecast Performance Between SARIMA and SETAR Models: An Application to Ghana Inflation Rate2011Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis

In recent years, many research works such as Tiao and Tsay (1994), Stock and Watson (1999), Chen et al. (2001), Clements and Jeremy (2001), Marcellino (2002), Laurini and Vieira (2005) and others have described the dynamic features of many macroeconomic variables as nonlinear. Using the approach of Keenan (1985) and Tsay (1989) this study shown that Ghana inflation rates from January 1980 to December 2009 follow a threshold nonlinear process.  In order to take into account the nonlinearity in the inflation rates we then apply a two regime nonlinear SETAR model to the inflation rates and then study both in-sample and out-of-sample forecast performance of this model by comparing it with the linear SARIMA model.

Based on the in-sample forecast assessment from the linear SARIMA and the nonlinear SETAR models, the forecast measure MAE and RMSE suggest that the nonlinear SETAR model outperform the linear SARIMA model. Also using multi-step-ahead forecast method we predicted and compared the out-of-sample forecast of the linear SARIMA and the nonlinear SETAR models over the forecast horizon of 12 months during the period of 2010:1 to 2010:12. From the results as suggested by MAE and RMSE, the forecast performance of the nonlinear SETAR models is superior to that of the linear SARIMA model in forecasting Ghana inflation rates.

Thought the nonlinear SETAR model is superior to the SARIMA model according to MAE and RMSE measure but using Diebold-Mariano test, we found no significant difference in their forecast accuracy for both in-sample and out-of-sample.

• 24.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Personality and Social Psychology Factors Explaining Sexism2011In: Journal of Individual Differences, ISSN 1614-0001, E-ISSN 2151-2299, Vol. 32, no 3, p. 153-160Article in journal (Refereed)

Previous research has almost exclusively examined sexism (negative attitudes toward women) from either a personality or a social-psychology perspective. In two studies (N = 379 and 182, respectively), we combine these perspectives and examine whether sexism is best explained by personality (Big-Five factors, social dominance orientation, and right-wing authoritarianism) or by social-psychological (group membership and group identification) variables - or by a combination of both approaches. Causal modeling and multiple regression analyses showed that, with the present set of variables, sexism was best explained by considering the combined influence of both personality- and social-psychology constructs. The findings imply that it is necessary to integrate various approaches to explain prejudice.

• 25.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Performance of Three Classification Techniques in Classifying Credit Applications Into Good Loans and Bad Loans: A Comparison2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis

The use of statistical classification techniques in classifying loan applications into good loans and bad loans gained importance with the exponential increase in the demand for credit. It is paramount to use a classification technique with a high predictive capacity to ensure the profitability of the business venture.

In this study we aim to compare the predictive capability of three classification techniques: 1) Logistic regression, 2) CART, and 3) random forests. We apply these techniques on German credit data using an 80:20 learning:test split, and compare the performance of the models fitted using the three classification techniques. The probability of default pi for each observation in the test set is calculated using the models fitted on the training dataset. Each test set sample xi is then classified into a good loan or a bad loan, based on a threshold , such that xi$\in$ bad loan class if pi  $\alpha$. We chose several $\alpha$ thresholds in order to compare the performance of each of the three classification techniques on five model suitability statistics: Accuracy, precision, negative predictive value, recall, and specificity.

None of the classifiers turned out to be best at all the five cross-validation statistics. However, logistic regression has the best performance at low probability of default thresholds. On the other hand, for higher thresholds, CART performs best in accuracy, precision, and specificity measures, while random forest performs best for negative predictive value and recall measures.

• 26.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Clinical Psychology in Healthcare.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Clinical Psychology in Healthcare. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Clinical Psychology in Healthcare. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health, Pediatrics. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Caring Sciences. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health, Pediatrics. Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Clinical Psychology in Healthcare. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Clinical Psychology in Healthcare.
Development of health-related quality of life and symptoms of anxiety and depression among persons diagnosed with cancer during adolescence: a 10-year follow-up study2016In: Psycho-Oncology, ISSN 1057-9249, E-ISSN 1099-1611, Vol. 25, no 5, p. 582-589Article in journal (Refereed)

Objective: The main aim was to investigate the development of health-related quality of life (HRQOL) and symptoms of anxiety and depression in a cohort diagnosed with cancer during adolescence from shortly after up to 10 years after diagnosis.

Methods: Participants (n = 61) completed the SF-36 and the HADS shortly; six, 12, and 18 months; and two, three, four, and 10 years (n = 28) after diagnosis. Polynomial change trajectories were used to model development.

Results: Polynomial change trajectories showed an initial increase which abated over time into a decrease which abated over time for the SF-36 subscales Mental Health and Vitality; an initial decline which abated over time into an increase for HADS anxiety; and an initial decline which abated over time into an increase which abated over time for HADS depression. The SF-36 mental component summary showed no change from two to 10 years after diagnosis whereas the SF-36 physical component summary showed an increase from two years after diagnosis which declined over time. Ten years after diagnosis 29% reported possible anxiety.

Conclusions: Development of HRQOL and symptoms of anxiety and depression appears to be nonlinear among persons diagnosed with cancer during adolescence. Well into permanent survivorship an increase in symptoms of anxiety is shown and approximately a third of the participants report possible anxiety. The findings indicate the need for: studies designed to pinpoint the times of highest psychological risk, clinical follow-up focusing on psychological problems, and development of effective psychological interventions for survivors of adolescent cancer

• 27.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
An Evaluation of Hypothesis Testing Methods for Equating Differences in Kernel EquatingManuscript (preprint) (Other academic)

In observed-score equating, hypothesis tests of equating differences are helpful in deciding which equating function is suitable. Here, a hypothesis testing procedure for item response theory (IRT) observed-score kernel equating using a Wald test is introduced. Simulations evaluating the Wald test when using IRT and log-linear models are conducted. The test with either IRT or log-linear models is shown to have high power and greatly outperform the Hommel multiple hypothesis testing method. The Wald test is applied to two datasets in both an equivalent groups design and a non-equivalent groups design, showing that the Wald test can provide different conclusions to other hypothesis testing methods in practice.

• 28.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Contributions to Kernel Equating2014Doctoral thesis, comprehensive summary (Other academic)

The statistical practice of equating is needed when scores on different versions of the same standardized test are to be compared. This thesis constitutes four contributions to the observed-score equating framework kernel equating.

Paper I introduces the open source R package kequate which enables the equating of observed scores using the kernel method of test equating in all common equating designs. The package is designed for ease of use and integrates well with other packages. The equating methods non-equivalent groups with covariates and item response theory observed-score kernel equating are currently not available in any other software package.

In paper II an alternative bandwidth selection method for the kernel method of test equating is proposed. The new method is designed for usage with non-smooth data such as when using the observed data directly, without pre-smoothing. In previously used bandwidth selection methods, the variability from the bandwidth selection was disregarded when calculating the asymptotic standard errors. Here, the bandwidth selection is accounted for and updated asymptotic standard error derivations are provided.

Item response theory observed-score kernel equating for the non-equivalent groups with anchor test design is introduced in paper III. Multivariate observed-score kernel equating functions are defined and their asymptotic covariance matrices are derived. An empirical example in the form of a standardized achievement test is used and the item response theory methods are compared to previously used log-linear methods.

In paper IV, Wald tests for equating differences in item response theory observed-score kernel equating are conducted using the results from paper III. Simulations are performed to evaluate the empirical significance level and power under different settings, showing that the Wald test is more powerful than the Hommel multiple hypothesis testing method. Data from a psychometric licensure test and a standardized achievement test are used to exemplify the hypothesis testing procedure. The results show that using the Wald test can provide different conclusions to using the Hommel procedure.

1. Performing the Kernel Method of Test Equating with the Package kequate
Open this publication in new window or tab >>Performing the Kernel Method of Test Equating with the Package kequate
2013 (English)In: Journal of Statistical Software, ISSN 1548-7660, E-ISSN 1548-7660, Vol. 55, no 6, p. 1-25Article in journal (Refereed) Published
##### Abstract [en]

In standardized testing it is important to equate tests in order to ensure that the test takers, regardless of the test version given, obtain a fair test. Recently, the kernel method of test equating, which is a conjoint framework of test equating, has gained popularity. The kernel method of test equating includes five steps: (1) pre-smoothing, (2) estimation of the score probabilities, (3) continuization, (4) equating, and (5) computing the standard error of equating and the standard error of equating difference. Here, an implementation has been made for six different equating designs: equivalent groups, single group, counterbalanced, non-equivalent groups with anchor test using either chain equating or post-stratification equating, and non-equivalent groups using covariates. An R package for the kernel method of test equating called kequate is presented. Included in the package are also diagnostic tools aiding in the search for a proper log-linear model in the pre-smoothing step for use in conjunction with the R function glm.

##### Place, publisher, year, edition, pages
American Statistical Association, 2013
##### Keywords
observed-score test equating, R package, kernel equating, item-response theory
##### National Category
Probability Theory and Statistics
Statistics
##### Identifiers
urn:nbn:se:uu:diva-208912 (URN)000325948000001 ()
Available from: 2013-10-23 Created: 2013-10-10 Last updated: 2017-12-06Bibliographically approved
2. Improving the Bandwidth Selection in Kernel Equating
Open this publication in new window or tab >>Improving the Bandwidth Selection in Kernel Equating
2014 (English)In: Journal of educational measurement, ISSN 0022-0655, E-ISSN 1745-3984, Vol. 51, no 3, p. 223-238Article in journal (Refereed) Published
##### Abstract [en]

We investigate the current bandwidth selection methods in kernel equating and propose a method based on Silverman's rule of thumb for selecting the bandwidth parameters. In kernel equating, the bandwidth parameters have previously been obtained by minimizing a penalty function. This minimization process has been criticized by practitioners for being too complex and that it does not offer sufficient smoothing in certain cases. In addition, the bandwidth parameters have been treated as constants in the derivation of the standard error of equating even when they were selected by considering the observed data. Here, the bandwidth selection is simplified, and modified standard errors of equating (SEEs) that reflect the bandwidth selection method are derived. The method is illustrated with real data examples and simulated data.

##### Place, publisher, year, edition, pages
Blackwell Publishing, 2014
##### Keywords
kernel equating, observed-score test equating
##### National Category
Probability Theory and Statistics
Statistics
##### Identifiers
urn:nbn:se:uu:diva-223988 (URN)10.1111/jedm.12044 (DOI)000341592200001 ()
Available from: 2014-04-29 Created: 2014-04-29 Last updated: 2017-12-05Bibliographically approved
3. Item Response Theory Observed-Score Kernel Equating
Open this publication in new window or tab >>Item Response Theory Observed-Score Kernel Equating
2017 (English)In: Psychometrika, ISSN 0033-3123, E-ISSN 1860-0980, Vol. 82, no 1, p. 46-66Article in journal (Refereed) Published
##### Abstract [en]

Item response theory (IRT) observed-score kernel equating is introduced for the non-equivalent groups with anchor test equating design using either chain equating or post-stratification equating. The equating function is treated in a multivariate setting and the asymptotic covariance matrices of IRT observed-score kernel equating functions are derived. Equating is conducted using the two-parameter and three-parameter logistic models with simulated data and data from a standardized achievement test. The results show that IRT observed-score kernel equating offers small standard errors and low equating bias under most settings considered.

##### Keywords
observed-score equating, item response theory, equipercentile equating, standard errors, NEAT design
##### National Category
Probability Theory and Statistics
##### Identifiers
urn:nbn:se:uu:diva-233484 (URN)10.1007/s11336-016-9528-7 (DOI)000394985400003 ()27743280 (PubMedID)
##### Funder
Swedish Research Council, 2014-578 Available from: 2014-10-21 Created: 2014-10-06 Last updated: 2017-04-20Bibliographically approved
4. An Evaluation of Hypothesis Testing Methods for Equating Differences in Kernel Equating
Open this publication in new window or tab >>An Evaluation of Hypothesis Testing Methods for Equating Differences in Kernel Equating
(English)Manuscript (preprint) (Other academic)
##### Abstract [en]

In observed-score equating, hypothesis tests of equating differences are helpful in deciding which equating function is suitable. Here, a hypothesis testing procedure for item response theory (IRT) observed-score kernel equating using a Wald test is introduced. Simulations evaluating the Wald test when using IRT and log-linear models are conducted. The test with either IRT or log-linear models is shown to have high power and greatly outperform the Hommel multiple hypothesis testing method. The Wald test is applied to two datasets in both an equivalent groups design and a non-equivalent groups design, showing that the Wald test can provide different conclusions to other hypothesis testing methods in practice.

##### National Category
Probability Theory and Statistics
##### Identifiers
urn:nbn:se:uu:diva-233486 (URN)
Available from: 2014-10-21 Created: 2014-10-06 Last updated: 2015-02-03
• 29.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Department of Statistics, USBE, Umeå University. Department of Statistics, USBE, Umeå University.
Performing the Kernel Method of Test Equating with the Package kequate2013In: Journal of Statistical Software, ISSN 1548-7660, E-ISSN 1548-7660, Vol. 55, no 6, p. 1-25Article in journal (Refereed)

In standardized testing it is important to equate tests in order to ensure that the test takers, regardless of the test version given, obtain a fair test. Recently, the kernel method of test equating, which is a conjoint framework of test equating, has gained popularity. The kernel method of test equating includes five steps: (1) pre-smoothing, (2) estimation of the score probabilities, (3) continuization, (4) equating, and (5) computing the standard error of equating and the standard error of equating difference. Here, an implementation has been made for six different equating designs: equivalent groups, single group, counterbalanced, non-equivalent groups with anchor test using either chain equating or post-stratification equating, and non-equivalent groups using covariates. An R package for the kernel method of test equating called kequate is presented. Included in the package are also diagnostic tools aiding in the search for a proper log-linear model in the pre-smoothing step for use in conjunction with the R function glm.

• 30.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Educational Testing Service.
Book review of M. J. Kolen & R. L. Brennan (2014) Test Equating, Scaling, and Linking: Methods and Practices Third Edition.2015In: Psychometrika, ISSN 0033-3123, E-ISSN 1860-0980, Vol. 80, no 3, p. 856-858Article, book review (Other academic)
• 31.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Educational Testing Service.
Improving the Bandwidth Selection in Kernel Equating2014In: Journal of educational measurement, ISSN 0022-0655, E-ISSN 1745-3984, Vol. 51, no 3, p. 223-238Article in journal (Refereed)

We investigate the current bandwidth selection methods in kernel equating and propose a method based on Silverman's rule of thumb for selecting the bandwidth parameters. In kernel equating, the bandwidth parameters have previously been obtained by minimizing a penalty function. This minimization process has been criticized by practitioners for being too complex and that it does not offer sufficient smoothing in certain cases. In addition, the bandwidth parameters have been treated as constants in the derivation of the standard error of equating even when they were selected by considering the observed data. Here, the bandwidth selection is simplified, and modified standard errors of equating (SEEs) that reflect the bandwidth selection method are derived. The method is illustrated with real data examples and simulated data.

• 32.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Sensitivity analysis of violations of the faithfulness assumption2014In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 84, no 7, p. 1608-1620Article in journal (Refereed)

We study the implication of violations of the faithfulness condition due to parameter cancellations on estimation of the directed acyclic graph (DAG) skeleton. Three settings are investigated: when (i) faithfulness is guaranteed (ii) faithfulness is not guaranteed and (iii) the parameter distributions are concentrated around unfaithfulness (near-unfaithfulness). In a simulation study, the effects of the different settings are compared using the parents and children (PC) and max–min parents and children (MMPC) algorithms. The results show that the performance in the faithful case is almost unchanged compared with the unrestricted case, whereas there is a general decrease in performance under the near-unfaithful case as compared with the unrestricted case. The response to near-unfaithful parameterizations is similar between the two algorithms, with the MMPC algorithm having higher true positive rates and the PC algorithm having lower false positive rates.

• 33.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Umeå University.
IRT Observed-score Kernel Equating2014Report (Other academic)

Item response theory (IRT) observed-score kernel equating is described for thenon-equivalent groups with anchor test equating design using either chain equating orpost-stratification equating. The equating function is treated in a multivariate setting andthe asymptotic covariance matrices of IRT observed-score kernel equating functions arederived. Equating is conducted using the two-parameter and three-parameter logisticmodels with simulated data and data from a standardized achievement test. The resultsshow that IRT observed-score kernel equating offers small standard errors and low equatingbias under most settings considered.

• 34.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics. Beijing Normal Univ, Beijing, Peoples R China..
Department of Statistics, USBE, Umeå University, Sweden..
Item Response Theory Observed-Score Kernel Equating2017In: Psychometrika, ISSN 0033-3123, E-ISSN 1860-0980, Vol. 82, no 1, p. 46-66Article in journal (Refereed)

Item response theory (IRT) observed-score kernel equating is introduced for the non-equivalent groups with anchor test equating design using either chain equating or post-stratification equating. The equating function is treated in a multivariate setting and the asymptotic covariance matrices of IRT observed-score kernel equating functions are derived. Equating is conducted using the two-parameter and three-parameter logistic models with simulated data and data from a standardized achievement test. The results show that IRT observed-score kernel equating offers small standard errors and low equating bias under most settings considered.

• 35.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Trust and Turnout: An Empirical Study of South African Voters2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis

Scholars have proposed the idea that trust influences individuals’ choice to vote or abstain. However, there is uncertainty about the composition of trust and its effect on voter turnout. The aim of this study is to explore the relationship between interpersonal and institutional trust and voter turnout in South Africa. Examining presently unused data for South Africa from the World Values Survey 2006 through exploratory and confirmatory factor analysis, the argument is advanced that trust is a multidimensional concept that may be modelled by multivariate measurements. A logistic factor score regression model shows that a one-unit increase of trust in public institutions on average increases the odds of voting by 9 % whereas trust in private institutions and interpersonal trust have no significant effects. The results imply that trust- strengthening actions may be of interest to South African public institutions to increase electoral participation and legitimise election outcomes.

• 36.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Testing For Normality of Censored Data2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis

In order to make statistical inference, that is drawing conclusions from a sample to describe a population, it is crucial to know the correct distribution of the data. This paper focused on censored data from the normal distribution. The purpose of this paper was to answer whether we can test if data comes from a censored normal distribution. This by using normality tests and tests designed for censored data and investigate if we got correct size of these tests. This has been carried out with simulations in the program R for left censored data. The results indicated that with increasing censoring normality tests failed to accept normality in a sample. On the other hand the censoring tests met the requirements with increasing censoring level, which was the most important conclusion in this paper.

• 37.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Ansträngning i OECD:s PISA-test: En studie om hur ansträngning påverkar antalet överhoppade matematikuppgifter för elever i Sverige2016Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis

The aim and focus of this study is to investigate how Swedish students’ effort affects the number of unanswered mathematical tasks for the PISA-tests in 2003 and 2012. The effort is measured partially by looking at students’ self-assessed effort invested in the test, but also by looking at how the count of unanswered tasks deviates in differ- ent parts of the test. Poisson regression is implemented as the primary method of investigation. The results from the regression indicates both that the students who reported a lower self-assessed effort tend to skip more tasks on average and also that students on average tend to skip more tasks in the end of the test. This indicates that the students’ effort is a crucial part to include in order to see how many tasks that are skipped in the test. It is also indicated that the effort is not constant during the whole test. The results also point out that the effect that effort has on unan- swered tasks is greater in 2003 compared to 2012. However, the count of unanswered tasks is on average higher for students in 2012.

• 38.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Estimating Companies’ Survival in Financial Crisis: Using the Cox Proportional Hazards Model2014Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis

This master thesis is aimed towards answering the question What is the contribution from a company’s sector with regards to its survival of a financial crisis? with the sub question Can we use survival analysis on financial data to answer this?. Thus survival analysis is used to answer our main question which is seldom used on financial data. This is interesting since it will study how well survival analysis can be used on financial data at the same time as it will evaluate if all companies experiences a financial crisis in the same way. The dataset consists of all companies traded on the Swedish stock market during 2008. The results show that the survival method is very suitable the data that is used. The sector a company operated in has a significant effect. However the power is to low too give any indication of specific differences between the different sectors. Further on it is found that the group of smallest companies had much better survival than larger companies.

• 39.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Financial Econometrics: A Comparison of GARCH type Model Performances when Forecasting VaR2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis

This essay investigates three different GARCH-models (GARCH, EGARCH and GJR-GARCH) along with two distributions (Normal and Student’s t), which are used to forecast the Value at Risk (VaR) for different return series. Seven major international equity indices are examined. The purpose of the essay is to answer which of the three models that is better at forecasting the VaR and which distribution is more appropriate.  The results show that the EGARCH(1,1)  is preferred for all indices included in the study.

• 40.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Unbiased simulation of stochastic differential equations using parametrix expansions2017In: Bernoulli, ISSN 1350-7265, E-ISSN 1573-9759, Vol. 23, no 3, p. 2028-2057Article in journal (Refereed)

In this article, we consider an unbiased simulation method for multidimensional diffusions based on the parametrix method for solving partial differential equations with Holder continuous coefficients. This Monte Carlo method which is based on an Euler scheme with random time steps, can be considered as an infinite dimensional extension of the Multilevel Monte Carlo method for solutions of stochastic differential equations with Holder continuous coefficients. In particular, we study the properties of the variance of the proposed method. In most cases, the method has infinite variance and therefore we propose an importance sampling method to resolve this issue.

• 41.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
On the Specification of Local Models in a Global Vector Autoregression: A Comparison of Markov-Switching Alternatives2014Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis

In this paper, focus is on the global vector autoregressive (GVAR) model. Its attractiveness

stems from an ability to incorporate global interdependencies when modeling local

economies. The model is based on a collection of local models, which in general are estimated as regular VAR models. This paper examines alternative specifications of the local

models by estimating them as regime-switching VAR models, where transition probabilities

between different states are studied using both constant and time-varying settings. The

results show that regime-switching models are appealing as they yield inferences about the

states of the economy, but these inferences are not guaranteed to be reasonable from an

economic point of view. Furthermore, the global solution of the model is in some cases

non-stationary when local models are regime-switching. The conclusion is that the regime-switching alternatives, while theoretically reasonable, are sensitive to the exact specification

used. At the same time, the issue of specifying the regime-switching models in such

a way that they perform adequately speaks in favor of the simpler, yet functional, basic

GVAR model.

• 42.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Swedish National Debt Office. Ministry of Finance, Sweden.
The importance of the financial system for the real economy2015Report (Other academic)

This paper analyses the importance of the nancial system for the real economy using a Bayesian VAR model for the macro economy, completed with financial variables, with priors on the steady states. The results suggest that i) a substantial part of the forecast error variance of GDPgrowth is attributed to shocks to the financial variables, indicating the importance of the financial system. ii) The suggested model produces an earlier and stronger signal regarding the probability of recession, compared to a model without financial variables. iii) Finally, and most striking, the augmented model's forecasts for 2008 and 2009, conditional on the development of the financial variables, clearly outperforms the macro model. Furthermore, this drastic improvement in modelling GDP during the crisis does not come at the expense of predictive power. In this respect, the augmented model performs as well as the standard macro model. Taken together, the results thus suggest that the proposed model presents an accessible possibility to analyse the macro-financial linkages and the GDP developments during a financial crisis.

• 43.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
A STUDY ON THE DCC-GARCH MODEL’S FORECASTING ABILITY WITH VALUE-AT-RISK APPLICATIONS ON THE SCANDINAVIAN FOREIGN EXCHANGE MARKET2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis

This thesis has treated the subject of DCC-GARCH model’s forecasting ability and Value-at- Risk applications on the Scandinavian foreign exchange market. The estimated models were based on daily opening foreign exchange spot rates in the period of 2004-2013, which captured the information in the financial crisis of 2008 and Eurozone crisis in the early 2010s. The forecasts were performed on a one-day rolling window in 2014. The results show that the DCC-GARCH model accurately predicted the fluctuation in the conditional correlation, although not with the correct magnitude. Furthermore, the DCC-GARCH model shows good Value-at-Risk forecasting performance for different portfolios containing the Scandinavian currencies.

• 44.
Uppsala University, Units outside the University, Office of Labour Market Policy Evaluation. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Centre for Research Ethics and Bioethics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics. Uppsala University, Units outside the University, Office of Labour Market Policy Evaluation. Uppsala University, Units outside the University, Office of Labour Market Policy Evaluation.
Parenthood and the Gender Gap in Pay2016In: Journal of Labor Economics, ISSN 0734-306X, Vol. 34, no 3, p. 545-579Article in journal (Refereed)

We compare the income and wage trajectories of women to those of their male partners before and after parenthood. Focusing on the within-couple gap allows us to control for both observed and unobserved attributes of the spouse and to estimate both short-and long-term effects of entering parenthood. We find that 15 years after the first child has been born, the male-female gender gaps in income and wages have increased by 32 and 10 percentage points, respectively. In line with a collective labor supply model, the magnitude of these effects depends on counterfactual relative incomes or wages within the family.

• 45.
Uppsala University, Units outside the University, Office of Labour Market Policy Evaluation.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics. Uppsala University, Units outside the University, Office of Labour Market Policy Evaluation.
Sick of family responsibilities?2019In: Empirical Economics, ISSN 0377-7332, E-ISSN 1435-8921Article in journal (Refereed)

This study estimates the effect of parenthood on the within-couple gender gap in paidsick leave. We find that as a result of parenthood, mothers more than double their sick leave compared with fathers. However, there is no corresponding effect on health measured by hospital stays. We also find that mothers’ income trajectory is strongly related to the magnitude of the effect: A less favorable income trajectory is associated with a larger effect of parenthood on the sick leave gap. Since mothers’ labor supply is measured 1 year prior to sick leave, this result suggests that the lower labor supply induces an increase in sick leave rather than the other way round.

• 46.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Swedish National Debt Office, Stockholm, Sweden. Ministry of Finance, Stockholm, Sweden.
The importance of the financial system for the real economy2017In: Empirical Economics, ISSN 0377-7332, E-ISSN 1435-8921, Vol. 53, no 4, p. 1553-1586Article in journal (Refereed)

This paper first describes financial variables that have been constructed to correspond to various channels in the transmission mechanism. Next, a Bayesian VAR model for the macroeconomy, with priors on the steady states, is augmented with these financial variables and estimated using Swedish data for 1989–2015. The results support three conclusions. First, the financial system is important and the strength of the results is dependent on identification, with the financial variables accounting for 10–25 % of the forecast error variance of Swedish GDP growth. Second, the suggested model produces an earlier signal regarding the probability of recession, compared to a model without financial variables. Third, the model’s forecasts for the deep downturn in 2008 and 2009, conditional on the development of the financial variables, outperform a macro-model that lacks financial variables. Furthermore, this improvement in modelling Swedish GDP growth during the financial crisis does not come at the expense of unconditional predictive power. Taken together, the results suggest that the proposed model presents an accessible possibility to analyse the macro-financial linkages and the GDP developments, especially during a financial crisis.

• 47.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
On the equivalence of confidence interval estimation based on frequentist model averagingand least-squares for the full model in linear regression2016Report (Other academic)

In many applications of linear regression models, model selection is vital. However, randomness due to model selection is commonly ignored in post-model selection inference. In order to account for the model selection uncertainty in these linear models, least squares frequentist model averaging has been proposed recently. In this paper, we show that the confidence interval from model averaging is asymptotically equivalent to the confidence interval from the full model. Furthermore, we demonstrate that this equivalence also holds in finite samples if the parameter of interest is a linear function of the regression coefficients.

• 48.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
On the least-squares model averaging interval estimator2018In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 47, no 1, p. 118-132Article in journal (Refereed)

In many applications of linear regression models, randomness due to model selection is commonly ignored in post-model selection inference. In order to account for the model selection uncertainty, least-squares frequentist model averaging has been proposed recently. We show that the confidence interval from model averaging is asymptotically equivalent to the confidence interval from the full model. The finite-sample confidence intervals based on approximations to the asymptotic distributions are also equivalent if the parameter of interest is a linear function of the regression coefficients. Furthermore, we demonstrate that this equivalence also holds for prediction intervals constructed in the same fashion.

• 49.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Estimating a VECM for a small open economy2018Report (Other academic)

One of the most popular ways to model macro economic variables is bythe vector error correction model (VECM). Besides forecasting and testing ofhypotheses, the  VECM is often used for calculating impulse responses, whichdescribe how shocks today aect the variables in the future. In economic theory,a small open economy denotes the economy of a country which is toosmall to inuence the surrounding world. The surrounding world can, for thisreason, be seen as exogenous relative to the economy of this small open economy.The main contribution of this paper is the proposal of how to estimatea VECM with exogeneity restrictions on both the short-run dynamics andthe short-run adjustment parameters between small open economies and thesurrounding world. A Monte Carlo simulation of impulse responses showsthat the proposed model is considerably more ecient compared to modelsfully or partially ignoring exogeneity. It is also shown that the empirical sizewhen testing for the number of long-run relations is closer to the nominalsize. Using two Swedish macroeconomic data sets the proposed method isapplied to estimate the models under weak exogeneity and Granger noncausality,respectively. We nd for some variables large deviances in impulseresponses between our proposed model incorporating both types of restrictionsand models using none or only one type of restriction, thus illustratingthe need for imposing the full set of restrictions instead of settling for just one.

• 50.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics. Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
A mixed-frequency Bayesian vector autoregression with a steady-state prior2018Report (Other academic)

We consider a Bayesian vector autoregressive (VAR) model allowing for an explicit priorspecication for the included variables' `steady states' (unconditional means) for data measuredat dierent frequencies. We propose a Gibbs sampler to sample from the posteriordistribution derived from a normal prior for the steady state and a normal-inverse-Wishart prior for the dynamics and error covariance. Moreover, we suggest a numerical algorithmfor computing the marginal data density that is useful for nding appropriate values for thenecessary hyperparameters. We evaluate the proposed model by applying it to a real-timedata set where we forecast Swedish GDP growth. The results indicate that the inclusionof high-frequency data improves the accuracy of low-frequency forecasts, in particular forshorter time horizons. The proposed model thus facilitates a simple and helpful way ofincorporating information about the long run through the steady-state prior as well asabout the near future through its ability to cope with mixed frequencies of the data.

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