Open AccessModeling the co-development of correlated processes with longitudinal and cross-construct effects.
Author(s) -
Yaacov Petscher,
Jamie Quinn,
Richard K. Wagner
Publication year - 2016
Publication title -
developmental psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.318
H-Index - 213
eISSN - 1939-0599
pISSN - 0012-1649
DOI - 10.1037/dev0000172
Subject(s) - latent growth modeling , psychology , multilevel model , psycinfo , developmental psychology , construct (python library) , structural equation modeling , fluency , latent variable , growth curve (statistics) , regression analysis , longitudinal data , random effects model , latent variable model , linear model , cognitive psychology , econometrics , statistics , meta analysis , computer science , mathematics , medicine , mathematics education , medline , political science , law , data mining , programming language
Conceptualizations of developmental trends are driven by the particular method used to analyze the period of change of interest. Various techniques exist to analyze developmental data, including individual growth curve analysis in observed and latent frameworks, cross-lagged regression to assess interrelations among variables, and multilevel frameworks that consider time as nested within individual. In this paper, we report on findings from a latent change score analysis of oral reading fluency and reading comprehension data from a longitudinal sample of approximately 16,000 students from first to fourth grade. Results highlight the utility of latent change score models compared to alternative specifications of linear and nonlinear quadratic latent growth models as well as implications for modeling change with correlated traits. (PsycINFO Database Record