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  • 1.
    Bali Swain, Ranjula
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Economics.
    Wallentin, Fan Yang
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science, Statistics.
    Does Microfinance Empower Women?: Evidence from Self Help Groups in India2007Report (Other academic)
    Abstract [en]

    Microfinance programs like the Self Help Bank Linkage Program in India have been increasingly promoted for their positive economic impact and the belief that they empower women. However, only a few studies rigorously examine the link between microfinance and women’s empowerment. This paper contributes by arguing that women empowerment takes place when women challenge the existing social norms and culture, to effectively improve their well being. It empirically validates this hypothesis by using quasi-experimental household sample data collected for five states in India for 2000 and 2003. A general structural model is estimated by employing appropriate techniques to treat the ordinal variables in  order to estimate the impact of the Self Help Group (SHG) on women empowerment for 2000 and 2003. The results strongly demonstrate that on average, there is a significant increase in the women empowerment of the SHG members group. No such significant change is observed however, for the members of the control group. The elegance of the result lies in the fact that the group of SHG participants show clear evidence of a significant and higher empowerment, while allowing for the possibility that some members might have been more empowered than others.

  • 2.
    Bali Swain, Ranjula
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Economics.
    Wallentin, Fan Yang
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    The impact of microfinance on factors empowering women: Differences in regional and delivery mechanisms in India’s SHG programme 2014Report (Other academic)
    Abstract [en]

    We examine how the impact on women empowerment varies with respect to the location and type of group linkage of the respondent. Using household survey data from five states in India, we correct for selection bias to estimate a structural equation model. Our results reveal that in the southern states of India empowerment of women takes place through economic factors. For the other states, we find a significant correlation between women empowerment and autonomy in women’s decision-making and network, communication and political participation respectively. We do not however find any differential causal impact of different delivery methods (linkage models).

  • 3.
    Bali Swain, Ranjula
    et al.
    MISUM, Stockholm School of Economics, Stockholm, Sweden.; Sodertorn Univ, Dept Econ, Stockholm, Sweden.
    Wallentin, Fan Yang
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    The Impact of Microfinance on Factors Empowering Women: Differences in Regional and Delivery Mechanisms in India’s SHG Programme2017In: Journal of Development Studies, ISSN 0022-0388, E-ISSN 1743-9140, Vol. 53, no 5, p. 684-699Article in journal (Refereed)
    Abstract [en]

    We examine how the impact on women’s empowerment varies with respect to the location and type of group linkage of the respondent. Using household survey data from five states in India, we correct for selection bias to estimate a structural equation model. Our results reveal that in the southern states of India empowerment of women takes place through economic factors. For the other states, we find a significant correlation between women’s empowerment and autonomy in women’s decision-making and network, communication and political participation respectively. We do not, however, find any differential causal impact of different delivery methods (linkage models).

  • 4.
    Bali Swain, Ranjula
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Economics.
    Yang Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Factors Empowering Women in Indian Self Help Group Program2012In: International review of applied economics, ISSN 0269-2171, E-ISSN 1465-3486, Vol. 26, no 4, p. 425-444Article in journal (Refereed)
    Abstract [en]

    We evaluate the impact of economic and non-economic factors on women’s empowerment of Self-Help Group (SHG) members. We estimate a structural equation model (SEM) and correct for ordinality in the data to account for the impact of the latent factors on women’s empowerment. Our SEM results reveal that for the SHG members, the economic factor is the most effective in empowering women. Greater autonomy and social attitudes also have a significant women empowerment impact.

  • 5.
    Bali Swain, Ranjula
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Economics.
    Yang Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    The impact of microfinance on factors empowering women: Regional and Delivery Mechanisms in India’s SHG Programme2014Report (Refereed)
    Abstract [en]

    We examine how the impact on women empowerment varies with respect to the location and type of group linkage of the respondent. Using household survey data from five states in India, we correct for selection bias to estimate a structural equation model. Our results reveal that in the southern states of India empowerment of women takes place through economic factors. For the other states, we find a significant correlation between women empowerment and autonomy in women’s decision-making and network, communication and political participation respectively. We do not however find any differential causal impact of different delivery methods (linkage models).

  • 6.
    Bali Swain, Ranjula
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Economics.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science, Statistics.
    Does microfinance empower women?: Evidence from self-help groups in India2009In: International review of applied economics, ISSN 0269-2171, E-ISSN 1465-3486, Vol. 23, no 5, p. 541-556Article in journal (Refereed)
    Abstract [en]

    Microfinance programmes like the Self Help Bank Linkage Program in India have been increasingly promoted for their positive economic impact and the belief that they empower women. However, only a few studies rigorously examine the link between microfinance and women's empowerment. This article contributes to this discussion by arguing that women's empowerment takes place when women challenge the existing social norms and culture, to effectively improve their well-being. It empirically validates this hypothesis by using quasi-experimental household sample data collected for five states in India for 2000 and 2003. A general model is estimated by employing appropriate techniques to treat the ordinal variables in order to estimate the impact of the Self Help Group (SHG) on women's empowerment for 2000 and 2003. The results strongly demonstrate that on average, there is a significant increase in the empowerment of women in the SHG members group. No such significant change is observed however, for the members of the control group. The elegance of the result lies in the fact that the group of SHG participants show clear evidence of a significant and higher empowerment, while allowing for the possibility that some members might have been more empowered than others.

  • 7. Goras, Camilla
    et al.
    Wallentin, Fan Yang
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Nilsson, Ulrica
    Ehrenberg, Anna
    Swedish translation and psychometric testing of the safety attitudes questionnaire (operating room version)2013In: BMC Health Services Research, ISSN 1472-6963, E-ISSN 1472-6963, Vol. 13, p. 104-Article in journal (Refereed)
    Abstract [en]

    Background: Tens of millions of patients worldwide suffer from avoidable disabling injuries and death every year. Measuring the safety climate in health care is an important step in improving patient safety. The most commonly used instrument to measure safety climate is the Safety Attitudes Questionnaire (SAQ). The aim of the present study was to establish the validity and reliability of the translated version of the SAQ. Methods: The SAQ was translated and adapted to the Swedish context. The survey was then carried out with 374 respondents in the operating room (OR) setting. Data was received from three hospitals, a total of 237 responses. Cronbach's alpha and confirmatory factor analysis (CFA) was used to evaluate the reliability and validity of the instrument. Results: The Cronbach's alpha values for each of the factors of the SAQ ranged between 0.59 and 0.83. The CFA and its goodness-of-fit indices (SRMR 0.055, RMSEA 0.043, CFI 0.98) showed good model fit. Intercorrelations between the factors safety climate, teamwork climate, job satisfaction, perceptions of management, and working conditions showed moderate to high correlation with each other. The factor stress recognition had no significant correlation with teamwork climate, perception of management, or job satisfaction. Conclusions: Therefore, the Swedish translation and psychometric testing of the SAQ (OR version) has good construct validity. However, the reliability analysis suggested that some of the items need further refinement to establish sound internal consistency. As suggested by previous research, the SAQ is potentially a useful tool for evaluating safety climate. However, further psychometric testing is required with larger samples to establish the psychometric properties of the instrument for use in Sweden.

  • 8.
    Jaensson, Maria
    et al.
    School of Health Sciences, Örebro University, Sweden.
    Falk-Brynhildsen, Karin
    School of Health Sciences, Örebro University.
    Gillespie, Brigid
    Griffith University, Australia.
    Yang Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Nilsson, Ulrica
    School of Health Sciences, Örebro University.
    Psychometric Validation of the PerceivedPerioperative Competence Scale-Revised inthe Swedish Context2018In: Journal of Perianesthesia Nursing, ISSN 1089-9472, E-ISSN 1532-8473, Vol. 3, no 4, p. 499-511Article in journal (Refereed)
    Abstract [en]

    Purpose: To psychometrically test the Perceived Perioperative Competence Scale-Revised (PPCS-R) in the Swedish context.

    Design: Cross-sectional survey.

    Methods: The 40-item PPCS-R was translated into Swedish using a forward-translation approach. A census of 2,902 registered nurse anesthetists (RNAs) and operating room (OR) nurses was drawn from a database of a national association in Sweden.

    Finding: The response rate was 39% (n = 1,033; 528 RNAs and 505 OR nurses). Cronbach alpha for each factor was 0.78 to 0.89 among OR nurses and 0.79 to 0.88 among RNAs. Confirmatory factor analysis showed good model fit in the six-factor model. Conclusions: Psychometric testing of the Swedish translation of the PPCS-R suggests a good construct validity, and the construct and its six factors are conceptually relevant among the Swedish OR nurses and RNAs.

  • 9.
    Jin, Shaobo
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Moustaki, Irini
    London School of Economics and Political Science.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Approximated penalized maximum likelihood for exploratory factor analysis: An orthogonal case2018In: Psychometrika, ISSN 0033-3123, E-ISSN 1860-0980, Vol. 83, no 3, p. 628-649Article in journal (Refereed)
    Abstract [en]

    The problem of penalized maximum likelihood (PML) for an exploratory factor analysis (EFA) model is studied in this paper. An EFA model is typically estimated using maximum likelihood and then the estimated loading matrix is rotated to obtain a sparse representation. Penalized maximum likelihood simultaneously fits the EFA model and produces a sparse loading matrix. To overcome some of the computational drawbacks of PML, an approximation to PML is proposed in this paper. It is further applied to an empirical dataset for illustration. A simulation study shows that the approximation naturally produces a sparse loading matrix and more accurately estimates the factor loadings and the covariance matrix, in the sense of having a lower mean squared error than factor rotations, under various conditions.

  • 10.
    Jin, Shaobo
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Asymptotic Robustness Study Of The Polychoric Correlation Estimation2017In: Psychometrika, ISSN 0033-3123, E-ISSN 1860-0980, Vol. 82, no 1, p. 67-85Article in journal (Refereed)
    Abstract [en]

    Asymptotic robustness against misspecification of the underlying distribution for the polychoric correlation estimation is studied. The asymptotic normality of the pseudo-maximum likelihood estimator is derived using the two-step estimation procedure. The t distribution assumption and the skew-normal distribution assumption are used as alternatives to the normal distribution assumption in a numerical study. The numerical results show that the underlying normal distribution can be substantially biased, even though skewness and kurtosis are not large. The skew-normal assumption generally produces a lower bias than the normal assumption. Thus, it is worth using a non-normal distributional assumption if the normal assumption is dubious.

  • 11.
    Jin, Shaobo
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Christoffersson, Anders
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Asymptotic Efficiency of the Pseudo-Maximum Likelihood Estimator in Multi-Group Factor Models with Pooled Data2016In: British Journal of Mathematical & Statistical Psychology, ISSN 0007-1102, E-ISSN 2044-8317, Vol. 69, no 1, p. 20-42Article in journal (Refereed)
    Abstract [en]

    A multi-group factor model is suitable for data originating from different strata. However, it often requires a relatively large sample size to avoid numerical issues such as non-convergence and non-positive definite covariance matrices. An alternative is to pool data from different groups in which a single-group factor model is fitted to the pooled data using maximum likelihood. In this paper, properties of pseudo-maximum likelihood (PML) estimators for pooled data are studied. The pooled data are assumed to be normally distributed from a single group. The resulting asymptotic efficiency of the PML estimators of factor loadings is compared with that of the multi-group maximum likelihood estimators. The effect of pooling is investigated through a two-group factor model. The variances of factor loadings for the pooled data are underestimated under the normal theory when error variances in the smaller group are larger. Underestimation is due to dependence between the pooled factors and pooled error terms. Small-sample properties of the PML estimators are also investigated using a Monte Carlo study.

  • 12.
    Katsikatsou, Myrsini
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Moustaki, Irini
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Jöreskog, Karl G.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Pairwise Likelihood Estimation for factor analysis models with ordinal data2011Report (Other academic)
    Abstract [en]

    Pairwise maximum likelihood (PML) estimation is developed for factor analysis models with ordinal data fitted both in an exploratory and confirmatory set-up, and its performance is studied and compared with full information maximum likelihood (FIML) and a three-stage limited information estimation method. More specifically, estimates and standard errors ob- tained from PML are compared with those obtained from FIML and those from robust un- weighted least squares (3S-RULS). All three methods provide very close estimates and stan- dard errors. However, the PML estimates and standard errors are on average slightly closer to FIML than the 3S-RULS are. The advantage of PML over FIML is mainly computational. The computational complexity of FIML increases with the number of factors or observed variables depending on the model formulation, while that of PML is affected by neither of them. Contrary to 3S-RULS, in PML, all model parameters are simultaneously estimated and therefore the final estimates reflect all the sampling variability. In the 3S-RULS method the standard errors of the parameter estimates in stage three do not incorporate the variability of the estimates obtained in step one. Furthermore, PML does not require the estimation of a weight matrix for computing correct standard errors. The performance of PML estimates and their estimated asymptotic standard errors are investigated through a simulation study where the effect of different models and sample sizes are studied. The bias and mean squared error of PML estimators and their standard errors are found to be small in all experimental conditions and decreasing with the sample size. 

  • 13.
    Katsikatsou, Myrsini
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Moustaki, Irini
    London School of Economics, Department of Statistics.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Jöreskog, Karl G.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Pairwise likelihood estimation for factor analysis models with ordinal data2012In: Computational Statistics & Data Analysis, ISSN 0167-9473, E-ISSN 1872-7352, Vol. 56, no 12, p. 4243-4258Article in journal (Refereed)
    Abstract [en]

    A pairwise maximum likelihood (PML) estimation method is developed for factor analysis models with ordinal data and fitted both in an exploratory and confirmatory set-up. The performance of the method is studied via simulations and comparisons with full information maximum likelihood (FIML) and three-stage limited information estimation methods, namely the robust unweighted least squares (3S-RULS) and robust diagonally weighted least squares (3S-RDWLS). The advantage of PML over FIML is mainly computational. Unlike PML estimation, the computational complexity of FIML estimation increases either with the number of factors or with the number of observed variables depending on the model formulation. Contrary to 3S-RULS and 3S-RDWLS estimation, PML estimates of all model parameters are obtained simultaneously and the PML method does not require the estimation of a weight matrix for the computation of correct standard errors. The simulation study on the performance of PML estimates and estimated asymptotic standard errors investigates the effect of different model and sample sizes. The bias and mean squared error of PML estimates and their standard errors are found to be small in all experimental conditions and decreasing with increasing sample size. Moreover, the PML estimates and their standard errors are found to be very close to those of FIML.

  • 14.
    Katsikatsou, Myrsini
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    On the identification of the unrestricted Thurstonian model for ranking data2011Report (Other academic)
    Abstract [en]

    The identification issues of the unrestricted Thurstonian model for ranking data is the focus of the current paper. The Thurstonian framework has been proved very influential in modeling ranking data. Within this framework, the objects to be ranked are associated with a latent continuous variable, often interpreted as utility. The unrestricted Thurstonian model has a central role in the related theory development but due to the discrete and comparative nature of ranking data it faces more serious identification problems than the indeterminacy of the latent scale origin and unit. Most researchers resort to the study of the unrestricted model referring to the differences of object utilities but then the inference on object utilities becomes tricky. Maydeu-Olivares & Böckenholt (2005) suggest a strategy to overcome the identification problem of the unrestricted model referring to object utilities but this requires many extra identification constraints, additional to the ones needed for defining the scale origin and unit. In the current paper, we study the suggested identification approach to investigate its general applicability. Our findings indicate that the estimates obtained based on this approach can be seriously biased when the extra constraints deviate from the true values of the parameters. Besides, the effect of the constraints is not uniform on all estimated parameters. 

  • 15.
    Kreiberg, David
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Söderström, Torsten
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Errors-in-variables identification using covariance matching and structural equation modeling2013In: Proc. 52nd Conference on Decision and Control, Piscataway, NJ: IEEE , 2013, p. 5852-5857Conference paper (Refereed)
  • 16.
    Kreiberg, David
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Söderström, Torsten
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Errors-in-variables system identification using structural equation modeling2016In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 66, p. 218-230Article in journal (Refereed)
    Abstract [en]

    Errors-in-variables (EIV) identification refers to the problem of consistently estimating linear dynamic systems whose output and input variables are affected by additive noise. Various solutions have been presented for identifying such systems. In this study, EIV identification using Structural Equation Modeling (SEM) is considered. Two schemes for how EIV Single-Input Single-Output (SISO) systems can be formulated as SEMs are presented. The proposed formulations allow for quick implementation using standard SEM software. By simulation examples, it is shown that compared to existing procedures, here represented by the covariance matching (CM) approach, SEM-based estimation provide parameter estimates of similar quality.

  • 17.
    Lundgren, Berndt Allan
    et al.
    KTH Royal Inst Technol, Dept Bldg & Construct Management, Stockholm, Sweden.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Measuring unobservable factors in residential developments: a structural equation approach2016In: Journal of European Real Estate Research, ISSN 1753-9269, E-ISSN 1753-9277, Vol. 9, no 3, p. 250-272Article in journal (Refereed)
    Abstract [en]

    Purpose – The purpose of this paper is to investigate how to measure the effect of unobservable factors on residential choice behavior in an attempt to advance the understanding of how to perform advanced market analysis. This research is important to residential developers, as the diversity of preferences is increasingly driven by lifestyle-based households and affluent households.

    Design/methodology/approach – Information about the pros and cons of renting an apartment in

    an ongoing residential development project in Stockholm came from interviews using the laddering technique. Qualitative data were subsequently analyzed using exploratory and confirmatory factor analysis to confirm which factors had the highest effect on an overall assessment of living in the development and a value-for-money conclusion.

    Findings – Among the potentially important factors identified, respondents who became residents perceived the development to be more noise-free than those who did not when stating the overall value of living in the development and making a value-for-money conclusion. The perception of noise differed between the two groups, meaning that those who did not become residents believed the development to be more exposed to noise. The standard of the apartment was the second most influential factor when stating the overall value of living in the development and making a value-for-money conclusion. The belief of being able to relax in the home environment had no significant effect on overall value for either group.

    Originality/value – The results show that confirmatory factor analysis can be used in measuring the effect of unobservable factors in residential choice behavior. The methodology presented may advise developers, architects or planners in evaluating those attributes that create value-for-money to improve, for example, overall design solutions in urban development projects.

  • 18.
    Nilsson, Ulrica
    et al.
    School of Health Sciences, Örebro University.
    Göras, Camilla
    School of Health Sciences, Örebro University.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Ehrenberg, Anna
    School of Health Sciences, Örebro University.
    Unbeck, Maria
    School of Health Sciences, Örebro University.
    The Swedish Safety Attitudes Questionnaire—Operating Room Version: Psychometric Properties in the Surgical Team2018In: Journal of Perianesthesia Nursing, ISSN 1089-9472, E-ISSN 1532-8473, Vol. 33, no 6, p. 935-945Article in journal (Refereed)
    Abstract [en]

    Purpose

    To validate the Swedish Safety Attitudes Questionnaire–operating room (SAQ-OR) version by re-evaluating its psychometric properties for the surgical team.

    Design

    Cross-sectional questionnaire study.

    Methods

    541 surgical team members including perioperative nurses, physicians, and licensed practical nurses at three Swedish hospitals were included.

    Findings

    For the total sample, the Cronbach’s α for the six factors ranged from 0.51 to 0.76. Goodness-of-fit analyses indicated that the six-factor model was acceptable and the factor loadings were statistically significant. The test of the hypothesized relationships among the factors showed a correlation from 0.936 to 0.042.

    Conclusions

    The refined Swedish version of the SAQ-OR is a reasonably reliable and acceptably valid instrument for the measurement of patient safety climate in the surgical team. However, the results related to the different analyses varied among the different professionals and further research, using larger samples, is needed to explore these differences, especially among the physicians.

  • 19.
    Olsson, Jan-Eric
    et al.
    Academic Primary Healthcare Centre, Huddinge, Sweden.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Toth-Pal, Eva
    Division of Family Medicine, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
    Ekblad, Solvig
    Academic Primary Healthcare Centre, Huddinge, Sweden.
    Bertilson, Bo
    Academic Primary Healthcare Centre, Huddinge, Sweden.
    Psychometric analysis of the Swedish version of the General Medical Council's multi source feedback questionnaires2017In: International Journal of Medical Education, ISSN 2042-6372, E-ISSN 2042-6372, Vol. 8, p. 252-261Article in journal (Refereed)
    Abstract [en]

    Objectives: To determine the internal consistency and the underlying components of our translated and adapted Swedish version of the General Medical Council's multisource feedback questionnaires (GMC questionnaires) for physicians and to confirm which aspects of good medical practice the latent variable structure reflected.

    Methods: From October 2015 to March 2016, residents in family medicine in Sweden were invited to participate in the study and to use the Swedish version to perform self-evaluations and acquire feedback from both their patients and colleagues. The validation focused on internal consistency and construct validity. Main outcome measures were Cronbach’s alpha coefficients, Principal Component Analysis, and Confirmatory Factor Analysis indices.

    Results: A total of 752 completed questionnaires from patients, colleagues, and residents were analysed. Of these, 213 comprised resident self-evaluations, 336 were feedback from residents’ patients, and 203 were feedback from residents’ colleagues. Cronbach’s alpha coefficients of the scores were 0.88 from patients, 0.93 from colleagues, and 0.84 in the self-evaluations. The Confirmatory Factor Analysis validated two models that fit the data reasonably well and reflected important aspects of good medical practice. The first model had two latent factors for patient-related items concerning empathy and consultation management, and the second model had five latent factors for colleague-related items, including knowledge and skills, attitude and approach, reflection and development, teaching, and trust.

    Conclusions: The current Swedish version seems to be a reliable and valid tool for formative assessment for resident physicians and their supervisors. This needs to be verified in larger samples.

  • 20.
    Rdz-Navarro, Karina
    et al.
    Univ Chile, Santiago, Chile.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Specification issues in nonlinear SEM: The moderation that wasn't2020In: Psicothema (Oviedo), ISSN 0214-9915, E-ISSN 1886-144X, Vol. 32, no 1, p. 115-121Article in journal (Refereed)
    Abstract [en]

    Background: Analysis of interaction or moderation effects between latent variables is a common requirement in the social sciences. However, when predictors are correlated, interaction and quadratic effects become more alike. making them difficult to distinguish. As a result, when data are drawn from a quadratic population model and the analysis model specifics interactions only, misleading results may be obtained.

    Method: This article addresses the consequences of different types of specification error in nonlinear structural equation models using a Monte Carlo study.

    Results: Results show that fitting a model with interactions when quadratic effects are present in the population will almost certainly lead to erroneous detection of moderation effects, and that the same is true in the opposite scenario. Simultaneous estimation of interactions and quadratic effects yields correct results.

    Conclusions: Simultaneous estimation of interaction and quadratic effects prevents detection of spurious or misleading nonlinear effects. Results are discussed and recommendations are offered to applied researchers.

  • 21.
    Scholtens, Sara
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Rydell, Ann-Margret
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    ADHD symptoms, academic achievement, self-perception of academic competence and future orientation: A longitudinal study2013In: Scandinavian Journal of Psychology, ISSN 0036-5564, E-ISSN 1467-9450, Vol. 54, no 3, p. 205-212Article in journal (Refereed)
    Abstract [en]

    In the investigation of the effect of attention deficit hyperactivity disorder (ADHD) symptoms on school careers there is a need to study the role of adolescent and childhood ADHD symptoms and academic achievement, and to incorporate measures that include the individual's perspective. Our aim was to gain an overview of the long-term development of school careers in relation to ADHD symptoms. We studied associations between ADHD symptoms and academic achievement at different time-points and future orientation at the end of high school, and assessed the role of self-perceptions of academic competence in these associations. Participants were 192 children (47% girls) with a range of ADHD symptoms taken from a community sample. Collecting data at three time points, in 6th, 11th and 12th grade we tested a structural equation model. Results showed that ADHD symptoms in 6th grade negatively affected academic achievement concurrently and longitudinally. ADHD symptoms in 11th grade negatively affected concurrent academic achievement and academic self-perception and future orientation in 12th grade. Academic achievement had a positive influence on academic self-perception and future orientation. Given the other factors, self-perception of academic competence did not contribute to outcomes. We concluded that early ADHD symptoms may cast long shadows on young people's academic progress. This happens mainly by way of stability in symptoms and relations to early low academic achievement.

  • 22.
    Yang-Wallentin, Fan
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Jöreskog, Karl
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Luo, Hao
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Confirmatory Factor Analysis of Ordinal Variables With Misspecified Models2010In: Structural Equation Modeling, ISSN 1070-5511, E-ISSN 1532-8007, Vol. 17, no 3, p. 392-423Article in journal (Refereed)
    Abstract [en]

    Ordinal variables are common in many empirical investigations in the social and behavioral sciences. Researchers often apply the maximum likelihood method to fit structural equation models to ordinal data. This assumes that the observed measures have normal distributions, which is not the case when the variables are ordinal. A better approach is to use polychoric correlations and fit the models using methods such as unweighted least squares (ULS), maximum likelihood (ML), weighted least squares (WLS), or diagonally weighted least squares (DWLS). In this simulation evaluation we study the behavior of these methods in combination with polychoric correlations when the models are misspecified. We also study the effect of model size and number of categories on the parameter estimates, their standard errors, and the common chi-square measures of fit when the models are both correct and misspecified. When used routinely, these methods give consistent parameter estimates but ULS, ML, and DWLS give incorrect standard errors. Correct standard errors can be obtained for these methods by robustification using an estimate of the asymptotic covariance matrix W of the polychoric correlations. When used in this way the methods are here called RULS, RML, and RDWLS.

  • 23.
    Yang-Wallentin, Fan
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science, Statistics.
    Yang-Hansen, Kajsa
    Department of Education, Gothenburg University.
    Non-linear structural equation modeling2009In: Structural Equation Modeling in Educational Research: Concepts and Applications / [ed] Timothy Teo and Myint Swe Khine, Rotterdam: SensePublishers , 2009, p. 317-328Chapter in book (Other academic)
    Abstract [en]

    Research in the social sciences often includes hypotheses concerning interactive or nonlinear effects on a given outcome latent variable. When it comes to estimating such effects, however, there is lack of consensus on how to do so properly, particularly when performing structural equation modeling (SEM). A plethora of methods have been proposed and discussed, including those de-scribed in Algina and Moulder (2001), Jaccard and Wan (1995), Joreskog and yang (1996,1997), Yang-Jonsson (1997,1998), Klein and Moosbrugger (2000), Klein and Muthen (2002), Marsh,Wen, and Hau (2004), Ping (1996a, 1996b), Schumacker and Marcoulides (1998), and Wall and Amemiya (2001, 2003). Most approaches to latent variable interactions are based on a product indicator methodology originated by Kenny and Judd (1984) that requires a level of technical and computational sophistication that renders them quite inaccessible to the average practitioner. The focus of this chapter is on the discussion of a technically straightforward approach using latent variable scores to estimating interactive and nonlinear effects within SEM. The next section, we will first describe LVS approach in a theoretical framework and in succeeding section, the approach will demonstrate in a practical manner using an empirical data.

    To illustrate how latent variable scores can be used to estimate nonlinear relationship between latent variables we will use Reading comprehension model as an example.

  • 24. Yuan, Ke-Hai
    et al.
    Wallentin, Fan Yang
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Bentler, Peter M.
    ML Versus MI for Missing Data With Violation of Distribution Conditions2012In: Sociological Methods & Research, ISSN 0049-1241, E-ISSN 1552-8294, Vol. 41, no 4, p. 598-629Article in journal (Refereed)
    Abstract [en]

    Normal-distribution-based maximum likelihood (ML) and multiple imputation (MI) are the two major procedures for missing data analysis. This article compares the two procedures with respects to bias and efficiency of parameter estimates. It also compares formula-based standard errors (SEs) for each procedure against the corresponding empirical SEs. The results indicate that parameter estimates by MI tend to be less efficient than those by ML; and the estimates of variance -covariance parameters by MI are also more biased. In particular, when the population for the observed variables possesses heavy tails, estimates of variance -covariance parameters by MI may contain severe bias even at relative large sample sizes. Although performing a lot better, ML parameter estimates may also contain substantial bias at smaller sample sizes. The results also indicate that, when the underlying population is close to normally distributed, SEs based on the sandwich-type covariance matrix and those based on the observed information matrix are very comparable to empirical SEs with either ML or MI. When the underlying distribution has heavier tails, SEs based on the sandwich-type covariance matrix for ML estimates are more reliable than those based on the observed information matrix. Both empirical results and analysis show that neither SEs based on the observed information matrix nor those based on the sandwich-type covariance matrix can provide consistent SEs in MI. Thus, ML is preferable to MI in practice, although parameter estimates by MI might still be consistent.

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