Latent profile transition analyses and growth mixture models: A very non‐technical guide for researchers in child and adolescent development-Reference-Cited by-同舟云学术

Latent profile transition analyses and growth mixture models: A very non‐technical guide for researchers in child and adolescent development

Published:2021-01 Issue:175 Volume:2021 Page:111-139
ISSN:1520-3247
Container-title:New Directions for Child and Adolescent Development
language:en
Short-container-title:New Directions for Child and Adolescent Development

Author:

Johnson Sara K.¹^ORCID

Affiliation:

1. Eliot‐Pearson Department of Child Study and Human Development Tufts University Medford MA 02145 USA

Publisher

Wiley

Subject

Developmental and Educational Psychology,Social Psychology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cad.20398

Reference62 articles.

1. Empathy Development in Adolescence Predicts Social Competencies in Adulthood

2. Asparouhov T. &Muthén B.(2012).Using Mplus TECH11 and TECH14 to test the number of latent classes. Mplus Web Notes: No. 14.https://www.statmodel.com/examples/webnotes/webnote14.pdf

3. Structural Equation Models and Mixture Models With Continuous Nonnormal Skewed Distributions

4. Distributional Assumptions of Growth Mixture Models: Implications for Overextraction of Latent Trajectory Classes.

5. Latent Class and Latent Transition Analysis

Cited by 41 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Mental health of young talented football players in an African context: A cross-sectional observational study;Comprehensive Psychiatry;2024-11

2. How pre-service teacher self-efficacy changes during the professional experience placement: a growth mixture model;The Australian Educational Researcher;2024-09-06

3. Using latent transition analysis to evaluate the impact of perceived threats on emotional and behavioral development;Child Development;2024-08-07

4. A latent profiling approach to foreign language enjoyment and L2 achievement;Journal of Multilingual and Multicultural Development;2024-07-18

5. Science career expectation and science-related motivation: a latent profile analysis using PISA 2015 data;International Journal of Science Education;2024-07-02