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Evaluation of Structural Equation Model Forests Performance to Identify Omitted Influential Covariates Struct. Equ. Model. (IF 2.5) Pub Date : 2024-11-07
John Alexander Silva Díaz, Moritz Heene, Andreas M. BrandmaierModel misspecification is typical in applied structural equation modeling (SEM). Traditional specification search methods, such as modification indices, search for misspecifications within the mode...
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Evaluating Local Model Misspecification with Modification Indices in Bayesian Structural Equation Modeling Struct. Equ. Model. (IF 2.5) Pub Date : 2024-10-29
Mauricio Garnier-Villarreal, Terrence D. JorgensenModel evaluation is a crucial step in SEM, consisting of two broad areas: global and local fit, where local fit indices are used to modify the original model. In the modification process, the modif...
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Addressing Missing Data in Latent Class Analysis When Using a Three-Step Estimation Approach Struct. Equ. Model. (IF 2.5) Pub Date : 2024-10-29
Sarah Depaoli, Fan Jia, Marieke VisserThis study specifically focuses on addressing the challenges related to employing missing data techniques when estimating a conditional Latent Class Analysis (LCA) model. In the context of a condit...
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The Effect of Measurement Error on Hypothesis Testing in Small Sample Structural Equation Modeling: A Comparison of Various Estimation Approaches Struct. Equ. Model. (IF 2.5) Pub Date : 2024-10-29
Jasper Bogaert, Wen Wei Loh, Florian Schuberth, Yves RosseelResearchers seeking valid statistical inference in the presence of measurement error often apply approaches that ignore measurement error. This may result in biased estimates, inflated type I error...
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Dynamic Structural Equation Modeling with Cycles Struct. Equ. Model. (IF 2.5) Pub Date : 2024-10-22
Bengt Muthén, Tihomir Asparouhov, Loes KeijsersCyclical phenomena are commonly observed in many areas of repeated measurements, especially with intensive longitudinal data. A typical example is circadian (24-hour) rhythm of physical measures su...
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A Growth of Hierarchical Autoregression Model for Capturing Individual Differences in Changes of Dynamic Characteristics of Psychological Processes Struct. Equ. Model. (IF 2.5) Pub Date : 2024-10-03
Yanling Li, Lindy Williams, Chelsea Muth, Saeideh Heshmati, Sy-Miin Chow, Zita OraveczSeveral methodological innovations have been advanced in the past decades that combine growth curve models (GCMs) with models of autoregressive (AR) processes. However, most of these approaches do ...
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Model Estimation Approaches for Fully-Latent Principal Stratification with Small Samples Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-25
Sooyong Lee, Adam Sales, Hyeon-Ah Kang, Tiffany A. WhittakerThis study investigated the performance of Bayesian fully-latent principal stratification (FLPS) models in estimating causal and principal effects in small-sample randomized control trials (RCTs) a...
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Latent Vector Autoregressive Modeling: A Stepwise Estimation Approach Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-25
Manuel T. Rein, Jeroen K. Vermunt, Kim De Roover, Leonie V. D. E. VogelsmeierResearchers often study dynamic processes of latent variables in everyday life, such as the interplay of positive and negative affect over time. An intuitive approach is to first estimate the measu...
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Review of Measurement Theory and Applications for the Social Sciences Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-24
Haley HallPublished in Structural Equation Modeling: A Multidisciplinary Journal (Ahead of Print, 2024)
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Assessing Heterogeneity of Correlation Matrices in Misspecified Meta-Analytic Structural Equation Models Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-09
Christian Bloszies, Tobias KochMeta-analytic structural equation modeling (MASEM) techniques are increasingly common tools to synthesize data across multiple studies. One popular approach is two-step MASEM, where study correlati...
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New Developments in Measurement Invariance Testing: An Overview and Comparison of EFA-Based Approaches Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-05
Philipp Sterner, Kim De Roover, David GoretzkoWhen comparing relations and means of latent variables, it is important to establish measurement invariance (MI). Most methods to assess MI are based on confirmatory factor analysis (CFA). Recently...
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Deriving Expected Values of Model Parameters When Using Sum Scores in Simulation Research Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-05
A. R. GeorgesonThere is increasing interest in using factor scores in structural equation models and there have been numerous methodological papers on the topic. Nevertheless, sum scores, which are computed from ...
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Efficient Adjusted Joint Significance Test and Sobel-Type Confidence Interval for Mediation Effect Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-04
Haixiang ZhangMediation analysis is an important statistical tool in many research fields, where the joint significance test is widely utilized for examining mediation effects. Nevertheless, the limitation of th...
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A Structural After Measurement Approach to Bifactor Predictive Models Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-05
Jinsoo Choi, Sunbeom Kwon, Bo ZhangThe bifactor model is becoming a popular tool for modeling hierarchical constructs. However, the bifactor predictive model, which uses both the general factor and all group factors to predict a cri...
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Research Design and Model Estimation Under the Partially Confirmatory Latent Variable Modeling Framework with Multi-Univariate Bayesian Lassos Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-04
Jinsong Chen, Yifan ZhangThis research builds upon existing developments of the partially confirmatory approach by introducing predictors and regularizations to two additional parameter matrices: structural and differentia...
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Review of Research and Evaluation in Education and Psychology: Integrating Diversity with Quantitative, Qualitative, and Mixed Methods (6th ed.) Struct. Equ. Model. (IF 2.5) Pub Date : 2024-08-09
Yosva Yosvi Br. SimbolonPublished in Structural Equation Modeling: A Multidisciplinary Journal (Ahead of Print, 2024)
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Shrinking Small Sample Problems in Multilevel Structural Equation Modeling via Regularization of the Sample Covariance Matrix Struct. Equ. Model. (IF 2.5) Pub Date : 2024-08-09
Julia-Kim Walther, Martin Hecht, Steffen ZitzmannSmall sample sizes pose a severe threat to convergence and accuracy of between-group level parameter estimates in multilevel structural equation modeling (SEM). However, in certain situations, such...
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The Impact of “Negligible” Cross-Loadings in Investigations of Measurement Invariance with MGCFA and MGESEM Struct. Equ. Model. (IF 2.5) Pub Date : 2024-08-05
Timothy R. Konold, Elizabeth A. Sanders, Kelvin AfolabiMeasurement invariance (MI) is an essential part of validity evidence concerned with ensuring that tests function similarly across groups, contexts, and time. Most evaluations of MI involve multigr...
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On the Estimation of Fit Indices for the Structural Part of a Model Struct. Equ. Model. (IF 2.5) Pub Date : 2024-08-05
Keke LaiWhen a researcher proposes an SEM model to explain the dynamics among some latent variables, the real question in model evaluation is the fit of the model’s structural part. A composite index that ...
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A Note on the Occurrence of the Illusory Between-Person Component in the Random Intercept Cross-Lagged Panel Model Struct. Equ. Model. (IF 2.5) Pub Date : 2024-07-29
Alexander Robitzsch, Oliver LüdtkeThe random intercept cross-lagged panel model (RICLPM) decomposes longitudinal associations between two processes X and Y into stable between-person associations and temporal within-person changes....
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Latent Variable Modeling of Social Networks with Directional Relations: An Exploration of Profile Similarity of Latent Factors Struct. Equ. Model. (IF 2.5) Pub Date : 2024-07-23
Haiyan Liu, Ren LiuStatistical analysis of networks has gained increasing popularity in social and psychological sciences. This study introduces a latent variable model for self-reported directional relations within ...
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Latent Interaction Effect in the CLPM Model: A Two-Step Multiple Imputation Analysis Struct. Equ. Model. (IF 2.5) Pub Date : 2024-07-16
Ming-Chi TsengThis study aims to estimate the latent interaction effect in the CLPM model through a two-step multiple imputation analysis. The estimation of within × within and between × within latent interactio...
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Evaluation of Maximal Reliability for Multidimensional Measuring Instruments Using Structural Equation Modeling Struct. Equ. Model. (IF 2.5) Pub Date : 2024-07-16
Tenko Raykov, Bingsheng ZhangMultidimensional measuring instruments are often used in behavioral, social, educational, marketing, and biomedical research. For these scales, the paper discusses how to find the optimal score bas...
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Incorporating Individual Differences in Conjoint Analysis: A Structural Equation Modeling Approach Struct. Equ. Model. (IF 2.5) Pub Date : 2024-07-16
Chung-Ping ChengIn the SEMWISE (Structural Equation Modeling for Within-Subject Experiments) framework, traditional conjoint analysis is treated as repeated measurements, which facilitates the incorporation of ind...
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Causal Mediation Analysis with the Parallel Process Latent Growth Curve Mediation Model Struct. Equ. Model. (IF 2.5) Pub Date : 2024-06-26
Xiao Liu, Lijuan WangIn parallel process latent growth curve mediation models, the mediation pathways from treatment to the intercept or slope of outcome through the intercept or slope of mediator are often of interest...
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Investigating Latent Interaction Effects in Multiple-Group Analysis in the Structural Equation Modeling Framework Struct. Equ. Model. (IF 2.5) Pub Date : 2024-06-25
Suyoung Kim, Sooyong Lee, Jiwon Kim, Tiffany A. WhittakerThis study aims to address a gap in the social and behavioral sciences literature concerning interaction effects between latent factors in multiple-group analysis. By comparing two approaches for e...
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An Alternative Prior for Estimation in High-Dimensional Settings Struct. Equ. Model. (IF 2.5) Pub Date : 2024-06-25
Michael Nagel, Lukas Fischer, Tim Pawlowski, Augustin KelavaBayesian estimations of complex regression models with high-dimensional parameter spaces require advanced priors, capable of addressing both sparsity and multicollinearity in the data. The Dirichle...
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SEM Approach to the Mediation Analysis of the Two-Condition Within-Subject Design Struct. Equ. Model. (IF 2.5) Pub Date : 2024-06-18
Eujin Park, Changsoon ParkThe effects of the two-condition within-subject (TCWS) conditional mediation model are developed using the SEM approach. The structural equation model for the within-subject mediator and the within...
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Joint Effects in Cross-Lagged Panel Research Using Structural Nested Mean Models Struct. Equ. Model. (IF 2.5) Pub Date : 2024-06-17
Jeroen D. Mulder, Satoshi Usami, Ellen L. HamakerA popular approach among psychological researchers for investigating causal relationships from panel data is cross-lagged panel modeling within the structural equation modeling (SEM) framework. How...
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Scale-Invariance, Equivariance and Dependency of Structural Equation Models Struct. Equ. Model. (IF 2.5) Pub Date : 2024-06-12
Ke-Hai Yuan, Ling Ling, Zhiyong ZhangData in social and behavioral sciences typically contain measurement errors and do not have predefined metrics. Structural equation modeling (SEM) is widely used for the analysis of such data, wher...
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Enhancing Model Fit Evaluation in SEM: Practical Tips for Optimizing Chi-Square Tests Struct. Equ. Model. (IF 2.5) Pub Date : 2024-06-10
Bang Quan Zheng, Peter M. BentlerThis paper aims to advocate for a balanced approach to model fit evaluation in structural equation modeling (SEM). The ongoing debate surrounding chi-square test statistics and fit indices has been...
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Matrix Decomposition Approach for Structural Equation Modeling as an Alternative to Covariance Structure Analysis and Its Theoretical Properties Struct. Equ. Model. (IF 2.5) Pub Date : 2024-05-31
Naoto YamashitaMatrix decomposition structural equation modeling (MDSEM) is introduced as a novel approach in structural equation modeling, contrasting with traditional structural equation modeling (SEM). MDSEM a...
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Investigating Structural Model Fit Evaluation Struct. Equ. Model. (IF 2.5) Pub Date : 2024-05-28
Xijuan Zhang, Hao WuA full structural equation model (SEM) typically consists of both a measurement model (describing relationships between latent variables and observed scale items) and a structural model (describing...
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Optimal Instrument Selection Using Bayesian Model Averaging for Model Implied Instrumental Variable Two Stage Least Squares Estimators Struct. Equ. Model. (IF 2.5) Pub Date : 2024-05-28
Teague R. Henry, Zachary F. Fisher, Kenneth A. BollenModel-Implied Instrumental Variable Two-Stage Least Squares (MIIV-2SLS) is a limited information, equation-by-equation, noniterative estimator for latent variable models. Associated with this estim...
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Minimal-Effect Testing, Equivalence Testing, and the Conventional Null Hypothesis Testing for the Analysis of Bi-Factor Models Struct. Equ. Model. (IF 2.5) Pub Date : 2024-05-28
Shunji Wang, Katerina M. Marcoulides, Jiashan Tang, Ke-Hai YuanA necessary step in applying bi-factor models is to evaluate the need for domain factors with a general factor in place. The conventional null hypothesis testing (NHT) was commonly used for such a ...
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Are the Signs of Factor Loadings Arbitrary in Confirmatory Factor Analysis? Problems and Solutions Struct. Equ. Model. (IF 2.5) Pub Date : 2024-05-28
Dandan Tang, Steven M. Boker, Xin TongThe replication crisis in social and behavioral sciences has raised concerns about the reliability and validity of empirical studies. While research in the literature has explored contributing fact...
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Can We Differentiate a Latent Growth Curve Model from Competitors? Evidence Based on Individual Case Residuals Struct. Equ. Model. (IF 2.5) Pub Date : 2024-05-28
Dan Wei, Peida Zhan, Hongyun LiuIn latent growth curve modeling (LGCM), overall fit indices have garnered increased disputation for model selection, and model fit evaluation based on the mean structure has becoming popularity. Th...
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Applying Benford’s Law for Assessing the Validity of Social Science Data Struct. Equ. Model. (IF 2.5) Pub Date : 2024-05-28
Ademola B. AjayiPublished in Structural Equation Modeling: A Multidisciplinary Journal (Ahead of Print, 2024)
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Estimating the Weight Matrix in Distributionally Weighted Least Squares Estimation: An Empirical Bayesian Solution Struct. Equ. Model. (IF 2.5) Pub Date : 2024-05-21
Han Du, Hao WuReal data are unlikely to be exactly normally distributed. Ignoring non-normality will cause misleading and unreliable parameter estimates, standard error estimates, and model fit statistics. For n...
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A Causal Framework for the Comparability of Latent Variables Struct. Equ. Model. (IF 2.5) Pub Date : 2024-04-30
Philipp Sterner, Florian Pargent, Dominik Deffner, David GoretzkoMeasurement invariance (MI) describes the equivalence of measurement models of a construct across groups or time. When comparing latent means, MI is often stated as a prerequisite of meaningful gro...
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Augmented Bifactor Models and Bifactor-(S-1) Models are Identical. A Comment on Zhang, Luo, Zhang, Sun & Zhang (2023) Struct. Equ. Model. (IF 2.5) Pub Date : 2024-04-30
Tobias Koch, Michael EidIn a recent study, Zhang et al. (2023) proposed the augmented oblique bifactor model as a new methodological contribution, in which an oblique bifactor model is augmented by one or more indicator(s...
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Review of Quantitative Methods for the Social Sciences: A Practical Introduction with Examples in R (2nd ed.) Struct. Equ. Model. (IF 2.5) Pub Date : 2024-04-16
Virginia Rosa da SilvaPublished in Structural Equation Modeling: A Multidisciplinary Journal (Vol. 31, No. 5, 2024)
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Handling Measurement Error and Omitted Confounders Considering Informativeness of the Confounding Effect under Mediation Modeling Struct. Equ. Model. (IF 2.5) Pub Date : 2024-04-10
Qian Zhang, Qi WangIn the article, we focused on the issues of measurement error and omitted confounders while conducting mediation analysis under experimental studies. Depending on informativeness of the confounders...
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Multilevel Factor Mixture Modeling: A Tutorial for Multilevel Constructs Struct. Equ. Model. (IF 2.5) Pub Date : 2024-04-05
Chunhua Cao, Yan Wang, Eunsook KimMultilevel factor mixture modeling (FMM) is a hybrid of multilevel confirmatory factor analysis (CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population heterog...
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Using SymPy (Symbolic Python) for Understanding Structural Equation Modeling Struct. Equ. Model. (IF 2.5) Pub Date : 2024-03-27
Joel S. Steele, Kevin J. GrimmStructural Equation Modeling (SEM) continues to grow in popularity with numerous articles, books, courses, and workshops available to help researchers become proficient with SEM quickly. However, f...
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To Be Long or To Be Wide: How Data Format Influences Convergence and Estimation Accuracy in Multilevel Structural Equation Modeling Struct. Equ. Model. (IF 2.5) Pub Date : 2024-03-27
Julia-Kim Walther, Martin Hecht, Benjamin Nagengast, Steffen ZitzmannA two-level data set can be structured in either long format (LF) or wide format (WF), and both have corresponding SEM approaches for estimating multilevel models. Intuitively, one might expect the...
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Overall Model Fit Does Not Imply Linearity in Longitudinal Structural Equation Models: Examining Linear Change Over Time Using Latent Variable Modeling Struct. Equ. Model. (IF 2.5) Pub Date : 2024-03-27
Tenko Raykov, Christine DiStefano, Natalja MenoldThis article is concerned with the assumption of linear temporal development that is often advanced in structural equation modeling-based longitudinal research. The linearity hypothesis is implemen...
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Causal Effects of Time-Varying Exposures: A Comparison of Structural Equation Modeling and Marginal Structural Models in Cross-Lagged Panel Research Struct. Equ. Model. (IF 2.5) Pub Date : 2024-03-19
Jeroen D. Mulder, Kim Luijken, Bas B. L. Penning de Vries, Ellen L. HamakerThe use of structural equation models for causal inference from panel data is critiqued in the causal inference literature for unnecessarily relying on a large number of parametric assumptions, and...
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Review of Practical Psychometrics: A Guide for Test Users Struct. Equ. Model. (IF 2.5) Pub Date : 2024-03-14
Musyaffa’ Ahmad, Muhammad FaisalPublished in Structural Equation Modeling: A Multidisciplinary Journal (Vol. 31, No. 5, 2024)
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Identifying Dynamic Shifts to Careless and Insufficient Effort Behavior in Questionnaire Responses; a Novel Approach and Experimental Validation Struct. Equ. Model. (IF 2.5) Pub Date : 2024-03-14
Zachary J. Roman, Patrick Schmidt, Jason M. Miller, Holger BrandtCareless and insufficient effort responding (C/IER) is a situation where participants respond to survey instruments without considering the item content. This phenomena adds noise to data leading t...
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Bayesian Structural Equation Models of Correlation Matrices Struct. Equ. Model. (IF 2.5) Pub Date : 2024-03-12
James Ohisei UanhoroWe present a method for Bayesian structural equation modeling of sample correlation matrices as correlation structures. The method transforms the sample correlation matrix to an unbounded vector us...
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Direct Discrepancy Dynamic Fit Index Cutoffs for Arbitrary Covariance Structure Models Struct. Equ. Model. (IF 2.5) Pub Date : 2024-03-12
Daniel McNeish, Melissa G. WolfDespite the popularity of traditional fit index cutoffs like RMSEA ≤ .06 and CFI ≥ .95, several studies have noted issues with overgeneralizing traditional cutoffs. Computational methods have been ...
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A Technique for Efficient Estimation of Dynamic Structural Equation Models: A Case Study Struct. Equ. Model. (IF 2.5) Pub Date : 2024-02-22
Leonidas Sakalauskas, Vytautas Dulskis, Darius PlikynasDynamic structural equation models (DSEM) are designed for time series analysis of latent structures. Inherent to the application of DSEM is model parameter estimation, which has to be addressed in...
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Fitting Cross-Lagged Panel Models with the Residual Structural Equations Approach Struct. Equ. Model. (IF 2.5) Pub Date : 2024-02-22
Ming-Chi TsengThis study simplifies the seven different cross-lagged panel models (CLPMs) by using the RSEM model for both inter-individual and intra-individual structures. In addition, the study incorporates th...
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Dynamic Structural Equation Models with Missing Data: Data Requirements on N and T Struct. Equ. Model. (IF 2.5) Pub Date : 2024-02-22
Yuan Fang, Lijuan WangDynamic structural equation modeling (DSEM) is a useful technique for analyzing intensive longitudinal data. A challenge of applying DSEM is the missing data problem. The impact of missing data on ...
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Bias-Adjusted Three-Step Multilevel Latent Class Modeling with Covariates Struct. Equ. Model. (IF 2.5) Pub Date : 2024-02-16
Johan Lyrvall, Zsuzsa Bakk, Jennifer Oser, Roberto Di MariWe present a bias-adjusted three-step estimation approach for multilevel latent class models (LC) with covariates. The proposed approach involves (1) fitting a single-level measurement model while ...
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D-Scoring Method of Measurement Classical and Latent Frameworks Struct. Equ. Model. (IF 2.5) Pub Date : 2024-02-16
Ademola B. AjayiPublished in Structural Equation Modeling: A Multidisciplinary Journal (Vol. 31, No. 4, 2024)
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Tackling Challenges in Data Pooling: Missing Data Handling in Latent Variable Models with Continuous and Categorical Indicators Struct. Equ. Model. (IF 2.5) Pub Date : 2024-02-16
Lihan Chen, Milica Miočević, Carl F. FalkData pooling is a powerful strategy in empirical research. However, combining multiple datasets often results in a large amount of missing data, as variables that are not present in some datasets e...
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Measurement Invariance is Not Sufficient for Meaningful and Valid Group Comparisons: A Note on Robitzsch and Lüdtke Struct. Equ. Model. (IF 2.5) Pub Date : 2024-02-16
Tenko RaykovThis note demonstrates that measurement invariance does not guarantee meaningful and valid group comparisons in multiple-population settings. The article follows on a recent critical discussion by ...
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Mediation Analyses of Intensive Longitudinal Data with Dynamic Structural Equation Modeling Struct. Equ. Model. (IF 2.5) Pub Date : 2024-01-30
Jie Fang, Zhonglin Wen, Kit-Tai HauCurrently, dynamic structural equation modeling (DSEM) and residual DSEM (RDSEM) are commonly used in testing intensive longitudinal data (ILD). Researchers are interested in ILD mediation models, ...