Pub Date : 2025-05-05DOI: 10.1080/10705511.2025.2484812
Mark H. C. Lai, Yichi Zhang, Meltem Ozcan, Winnie Wing-Yee Tse, Alexander Miles
{"title":"f MACS : Generalizing d MACS Effect Size for Measurement Noninvariance with Multiple Groups and Multiple Grouping Variables","authors":"Mark H. C. Lai, Yichi Zhang, Meltem Ozcan, Winnie Wing-Yee Tse, Alexander Miles","doi":"10.1080/10705511.2025.2484812","DOIUrl":"https://doi.org/10.1080/10705511.2025.2484812","url":null,"abstract":"","PeriodicalId":21964,"journal":{"name":"Structural Equation Modeling: A Multidisciplinary Journal","volume":"7 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144193797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-02-13DOI: 10.1080/10705511.2025.2452884
Hyungeun Oh, Michael D Hunter, Sy-Miin Chow
Dynamic Structural Equation Models (DSEMs) integrate multilevel modeling, time series analysis, and structural equation modeling within a Bayesian estimation framework, offering a versatile tool for analyzing intensive longitudinal data (ILD). However, the impact of measurement structure misspecification in DSEMs, especially under varying reliability conditions and model complexities, remains underexplored. Our Monte Carlo simulation revealed that omitting measurement errors when present led to severe biases in dynamic parameters regardless of reliability conditions, though power remained high. Increasing the number of participants and time points ameliorated but did not eliminate all biases. A single-indicator DSEMs with a measurement structure using composite scores showed similar performance to multiple indicators DSEMs. Empirical applications showed discrepancies in dynamic parameters based on the number of indicators and measurement structures used. Leveraging these findings, we provide design recommendations, functions for extending reliability indices from single-indicator to multiple-indicator models, and guidelines for power evaluations under different reliability conditions.
{"title":"Measurement Model Misspecification in Dynamic Structural Equation Models: Power, Reliability, and Other Considerations.","authors":"Hyungeun Oh, Michael D Hunter, Sy-Miin Chow","doi":"10.1080/10705511.2025.2452884","DOIUrl":"10.1080/10705511.2025.2452884","url":null,"abstract":"<p><p>Dynamic Structural Equation Models (DSEMs) integrate multilevel modeling, time series analysis, and structural equation modeling within a Bayesian estimation framework, offering a versatile tool for analyzing intensive longitudinal data (ILD). However, the impact of measurement structure misspecification in DSEMs, especially under varying reliability conditions and model complexities, remains underexplored. Our Monte Carlo simulation revealed that omitting measurement errors when present led to severe biases in dynamic parameters regardless of reliability conditions, though power remained high. Increasing the number of participants and time points ameliorated but did not eliminate all biases. A single-indicator DSEMs with a measurement structure using composite scores showed similar performance to multiple indicators DSEMs. Empirical applications showed discrepancies in dynamic parameters based on the number of indicators and measurement structures used. Leveraging these findings, we provide design recommendations, functions for extending reliability indices from single-indicator to multiple-indicator models, and guidelines for power evaluations under different reliability conditions.</p>","PeriodicalId":21964,"journal":{"name":"Structural Equation Modeling: A Multidisciplinary Journal","volume":"32 3","pages":"511-528"},"PeriodicalIF":3.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12183645/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144485705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2024-12-16DOI: 10.1080/10705511.2024.2429544
Jonathan J Park, Zachary F Fisher, Michael D Hunter, Chad Shenk, Michael Russell, Peter C M Molenaar, Sy-Miin Chow
Many of the advancements reconciling individual- and group-level results have occurred in the context of a discrete-time modeling framework. Discrete-time models are intuitive and offer relatively simple interpretations for the resulting dynamic structures; however, they do not possess the flexibility of models fitted in the continuous-time framework. We introduce ct-gimme, a continuous-time extension of the group iterative multiple model estimation (GIMME; Gates & Molenaar, 2012) procedure which enables researchers to fit complex, high dimensional dynamic networks in continuous-time. Our results indicate that ct-gimme outperforms model fitting in continuous-time by pooling information across multiple subjects. Likewise, ct-gimme outperforms group-level model fitting in the presence of within-sample heterogeneity. We conclude with an empirical illustration and highlight limitations of the approach relating to identification of meaningful starting values.
{"title":"Unsupervised Model Construction in Continuous-Time.","authors":"Jonathan J Park, Zachary F Fisher, Michael D Hunter, Chad Shenk, Michael Russell, Peter C M Molenaar, Sy-Miin Chow","doi":"10.1080/10705511.2024.2429544","DOIUrl":"10.1080/10705511.2024.2429544","url":null,"abstract":"<p><p>Many of the advancements reconciling individual- and group-level results have occurred in the context of a discrete-time modeling framework. Discrete-time models are intuitive and offer relatively simple interpretations for the resulting dynamic structures; however, they do not possess the flexibility of models fitted in the continuous-time framework. We introduce ct-gimme, a continuous-time extension of the group iterative multiple model estimation (GIMME; Gates & Molenaar, 2012) procedure which enables researchers to fit complex, high dimensional dynamic networks in continuous-time. Our results indicate that ct-gimme outperforms <math><mi>N</mi> <mo>=</mo> <mn>1</mn></math> model fitting in continuous-time by pooling information across multiple subjects. Likewise, ct-gimme outperforms group-level model fitting in the presence of within-sample heterogeneity. We conclude with an empirical illustration and highlight limitations of the approach relating to identification of meaningful starting values.</p>","PeriodicalId":21964,"journal":{"name":"Structural Equation Modeling: A Multidisciplinary Journal","volume":"32 3","pages":"377-399"},"PeriodicalIF":3.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12083780/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144094829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-07DOI: 10.1080/10705511.2024.2417866
John Alexander Silva Díaz, Moritz Heene, Andreas M. Brandmaier
Model misspecification is typical in applied structural equation modeling (SEM). Traditional specification search methods, such as modification indices, search for misspecifications within the mode...
{"title":"Evaluation of Structural Equation Model Forests Performance to Identify Omitted Influential Covariates","authors":"John Alexander Silva Díaz, Moritz Heene, Andreas M. Brandmaier","doi":"10.1080/10705511.2024.2417866","DOIUrl":"https://doi.org/10.1080/10705511.2024.2417866","url":null,"abstract":"Model misspecification is typical in applied structural equation modeling (SEM). Traditional specification search methods, such as modification indices, search for misspecifications within the mode...","PeriodicalId":21964,"journal":{"name":"Structural Equation Modeling: A Multidisciplinary Journal","volume":"61 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142597247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-29DOI: 10.1080/10705511.2024.2410240
Sarah Depaoli, Fan Jia, Marieke Visser
This 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...
{"title":"Addressing Missing Data in Latent Class Analysis When Using a Three-Step Estimation Approach","authors":"Sarah Depaoli, Fan Jia, Marieke Visser","doi":"10.1080/10705511.2024.2410240","DOIUrl":"https://doi.org/10.1080/10705511.2024.2410240","url":null,"abstract":"This 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...","PeriodicalId":21964,"journal":{"name":"Structural Equation Modeling: A Multidisciplinary Journal","volume":"7 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142574437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Researchers 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...
{"title":"The Effect of Measurement Error on Hypothesis Testing in Small Sample Structural Equation Modeling: A Comparison of Various Estimation Approaches","authors":"Jasper Bogaert, Wen Wei Loh, Florian Schuberth, Yves Rosseel","doi":"10.1080/10705511.2024.2398759","DOIUrl":"https://doi.org/10.1080/10705511.2024.2398759","url":null,"abstract":"Researchers 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...","PeriodicalId":21964,"journal":{"name":"Structural Equation Modeling: A Multidisciplinary Journal","volume":"27 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142574438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-29DOI: 10.1080/10705511.2024.2413128
Mauricio Garnier-Villarreal, Terrence D. Jorgensen
Model 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...
模型评估是 SEM 的关键步骤，包括两大方面：全局拟合和局部拟合，其中局部拟合指数用于修改原始模型。在修改过程中，修改...
{"title":"Evaluating Local Model Misspecification with Modification Indices in Bayesian Structural Equation Modeling","authors":"Mauricio Garnier-Villarreal, Terrence D. Jorgensen","doi":"10.1080/10705511.2024.2413128","DOIUrl":"https://doi.org/10.1080/10705511.2024.2413128","url":null,"abstract":"Model 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...","PeriodicalId":21964,"journal":{"name":"Structural Equation Modeling: A Multidisciplinary Journal","volume":"7 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142556227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-22DOI: 10.1080/10705511.2024.2406510
Bengt Muthén, Tihomir Asparouhov, Loes Keijsers
Cyclical 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...
{"title":"Dynamic Structural Equation Modeling with Cycles","authors":"Bengt Muthén, Tihomir Asparouhov, Loes Keijsers","doi":"10.1080/10705511.2024.2406510","DOIUrl":"https://doi.org/10.1080/10705511.2024.2406510","url":null,"abstract":"Cyclical 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...","PeriodicalId":21964,"journal":{"name":"Structural Equation Modeling: A Multidisciplinary Journal","volume":"24 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142490818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Several 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 ...
{"title":"A Growth of Hierarchical Autoregression Model for Capturing Individual Differences in Changes of Dynamic Characteristics of Psychological Processes","authors":"Yanling Li, Lindy Williams, Chelsea Muth, Saeideh Heshmati, Sy-Miin Chow, Zita Oravecz","doi":"10.1080/10705511.2024.2402328","DOIUrl":"https://doi.org/10.1080/10705511.2024.2402328","url":null,"abstract":"Several 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 ...","PeriodicalId":21964,"journal":{"name":"Structural Equation Modeling: A Multidisciplinary Journal","volume":"124 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142448727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-25DOI: 10.1080/10705511.2024.2402331
Sooyong Lee, Adam Sales, Hyeon-Ah Kang, Tiffany A. Whittaker
This 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...
{"title":"Model Estimation Approaches for Fully-Latent Principal Stratification with Small Samples","authors":"Sooyong Lee, Adam Sales, Hyeon-Ah Kang, Tiffany A. Whittaker","doi":"10.1080/10705511.2024.2402331","DOIUrl":"https://doi.org/10.1080/10705511.2024.2402331","url":null,"abstract":"This 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...","PeriodicalId":21964,"journal":{"name":"Structural Equation Modeling: A Multidisciplinary Journal","volume":"36 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142325563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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