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Sehee Hong

Showing results (1-10 of 15) with videos related to

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Frontiers in Psychology|February 14, 2022
The Impact of Imposing Equality Constraints on Residual Variances Across Classes in Regression Mixture ModelsJeongwon Choi, Sehee Hong
Educational and Psychological Measurement|July 16, 2021
Growth Mixture Modeling With Nonnormal Distributions: Implications for Data TransformationYeji Nam, Sehee Hong
Frontiers in Psychology|July 19, 2021
Adequate Sample Sizes for a Three-Level Growth ModelEunsoo Lee, Sehee Hong
Educational and Psychological Measurement|December 19, 2018
A Comparison of Mixture Modeling Approaches in Latent Class Models With External Variables Under Small SamplesUnkyung No, Sehee Hong
Educational and Psychological Measurement|March 3, 2023
Evaluating the Quality of Classification in Mixture Model SimulationsYoona Jang, Sehee Hong
Educational and Psychological Measurement|September 27, 2021
Multiple Group Analysis in Multilevel Data Across Within-Level Groups: A Comparison of Multilevel Factor Mixture Modeling and Multilevel Multiple-Indicators Multiple-Causes ModelingSookyoung Son, Sehee Hong
International Journal of Environmental Research and Public Health|March 3, 2021
Profiles of Working Moms' Daily Time Use: Exploring Their Impact on LeisureYoungseo Kim, Sehee Hong
Psychological Reports|March 29, 2018
Comparisons of Multilevel Modeling and Structural Equation Modeling Approaches to Actor-Partner Interdependence ModelSehee Hong, Soyoung Kim
Frontiers in Psychology|March 22, 2021
The Impact of Ignoring a Crossed Factor in Cross-Classified Multilevel ModelingSoyoung Kim, Yoonhwa Jeong, Sehee Hong
Educational and Psychological Measurement|October 18, 2019
Comparing the Robustness of Stepwise Mixture Modeling With Continuous Nonnormal Distal OutcomesMyungho Shin, Unkyung No, Sehee Hong
Pageof 2

Showing results (1-10 of 15) with videos related to

Sort By:
Pageof 2
Frontiers in Psychology|February 14, 2022
The Impact of Imposing Equality Constraints on Residual Variances Across Classes in Regression Mixture ModelsJeongwon Choi, Sehee Hong
Educational and Psychological Measurement|July 16, 2021
Growth Mixture Modeling With Nonnormal Distributions: Implications for Data TransformationYeji Nam, Sehee Hong
Frontiers in Psychology|July 19, 2021
Adequate Sample Sizes for a Three-Level Growth ModelEunsoo Lee, Sehee Hong
Educational and Psychological Measurement|December 19, 2018
A Comparison of Mixture Modeling Approaches in Latent Class Models With External Variables Under Small SamplesUnkyung No, Sehee Hong
Educational and Psychological Measurement|March 3, 2023
Evaluating the Quality of Classification in Mixture Model SimulationsYoona Jang, Sehee Hong
Educational and Psychological Measurement|September 27, 2021
Multiple Group Analysis in Multilevel Data Across Within-Level Groups: A Comparison of Multilevel Factor Mixture Modeling and Multilevel Multiple-Indicators Multiple-Causes ModelingSookyoung Son, Sehee Hong
International Journal of Environmental Research and Public Health|March 3, 2021
Profiles of Working Moms' Daily Time Use: Exploring Their Impact on LeisureYoungseo Kim, Sehee Hong
Psychological Reports|March 29, 2018
Comparisons of Multilevel Modeling and Structural Equation Modeling Approaches to Actor-Partner Interdependence ModelSehee Hong, Soyoung Kim
Frontiers in Psychology|March 22, 2021
The Impact of Ignoring a Crossed Factor in Cross-Classified Multilevel ModelingSoyoung Kim, Yoonhwa Jeong, Sehee Hong
Educational and Psychological Measurement|October 18, 2019
Comparing the Robustness of Stepwise Mixture Modeling With Continuous Nonnormal Distal OutcomesMyungho Shin, Unkyung No, Sehee Hong
Pageof 2