%0 Report %1 sokolov2019sensitivity %A Sokolov, Boris %B Higher School of Economics Research Paper %C Moscow %D 2019 %K 2019 EVS EVS_contra EVS_input2019 EVS_surv FDZ_IUP GS english jak kbe techreport text unchecked %N WP BRP 86/SOC/2019 %P 45 %R https://dx.doi.org/10.2139/ssrn.3417157 %T Sensitivity of Goodness of Fit Indices to Lack of Measurement Invariance with Categorical Indicators and Many Groups %U https://dx.doi.org/10.2139/ssrn.3417157 %X Using Monte Carlo simulation experiments, this paper examines the performance of popular SEM goodness-of-fit indices, namely CFI, TLI, RMSEA, and SRMR, with respect to a specific task of measurement invariance testing with categorical data and many groups (10-50 groups). Study factors include the number of groups, the level of non-invariance in the data, and the absence/presence of model misspecifications other than non-invariance. In sum, the study design yields a total of 81 conditions. All simulated data sets are analyzed using two popular SEM estimators, MLR and WLSMV. The main contribution of this paper to the methodological literature on cross-cultural survey research is that it produces revised guidelines for evaluating the goodness of fit of invariance MGCFA models with many groups.

@techreport{sokolov2019sensitivity, abstract = {Using Monte Carlo simulation experiments, this paper examines the performance of popular SEM goodness-of-fit indices, namely CFI, TLI, RMSEA, and SRMR, with respect to a specific task of measurement invariance testing with categorical data and many groups (10-50 groups). Study factors include the number of groups, the level of non-invariance in the data, and the absence/presence of model misspecifications other than non-invariance. In sum, the study design yields a total of 81 conditions. All simulated data sets are analyzed using two popular SEM estimators, MLR and WLSMV. The main contribution of this paper to the methodological literature on cross-cultural survey research is that it produces revised guidelines for evaluating the goodness of fit of invariance MGCFA models with many groups.}, added-at = {2019-12-18T17:49:08.000+0100}, address = {Moscow}, author = {Sokolov, Boris}, biburl = {https://www.bibsonomy.org/bibtex/225190b48559f4c2de14d7675486549d0/gesis_forschbib}, description = {study data-doi gesis-study_no }, doi = {https://dx.doi.org/10.2139/ssrn.3417157}, institution = {Higher School of Economics (HSE)}, interhash = {4e0275702be2087b481dd2cab9dabfca}, intrahash = {25190b48559f4c2de14d7675486549d0}, keywords = {2019 EVS EVS_contra EVS_input2019 EVS_surv FDZ_IUP GS english jak kbe techreport text unchecked}, language = {english}, note = {https://dx.doi.org/10.2139/ssrn.3417157. (EVS)}, number = {WP BRP 86/SOC/2019}, pages = 45, series = {Higher School of Economics Research Paper}, timestamp = {2019-12-19T09:44:01.000+0100}, title = {Sensitivity of Goodness of Fit Indices to Lack of Measurement Invariance with Categorical Indicators and Many Groups}, url = {https://dx.doi.org/10.2139/ssrn.3417157}, year = 2019 }