Related Experiment Video
Updated: Mar 26, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Mathew Effects in Reading: A Comparison of Latent Growth Curve Models and Simplex Models with Structured Means
Abstract:
The Matthew effect hypothesis in reading predicts that the gap between good and poor readers increases with time. Although, intuitively appealing, the Matthew effect has hardly been empirically studied in longitudinal studies of reading. Two competing longitudinal models were used to represent the Matthew effect hypothesis: the Latent Growth Curve model and the Simplex model with structured means. It is argued that on the basis of theoretical and empirical arguments the Simplex model should be preferred to represent and analyze the Matthew effect hypothesis. However, the results of the Simplex models imply that conceptual refinement and clarification of Matthew effects in reading are needed.
More Related Videos
Related Concept Videos
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Population Growth
Exponential Equations for Modeling Growth
Regression Toward the Mean
Modeling with Differential Equations
Growth Models with Integration: Problem Solving

