11 research outputs found
Eliminating Aggregation Bias in Experimental Research: Random Coefficient Analysis as an Alternative to Performing a ‘by-subjects’ and/or ‘by-items’ ANOVA
Confidence intervals in within-subject designs: A simpler solution to Loftus and Masson's method
Latent Class Growth Modelling: A Tutorial
The present work is an introduction to Latent Class Growth Modelling (LCGM). LCGM is a semi-parametric statistical technique used to analyze longitudinal data. It is used when the data follows a pattern of change in which both the strength and the direction of the relationship between the independent and dependent variables differ across cases. The analysis identifies distinct subgroups of individuals following a distinct pattern of change over age or time on a variable of interest. The aim of the present tutorial is to introduce readers to LCGM and provide a concrete example of how the analysis can be performed using a real-world data set and the SAS software package with accompanying PROC TRAJ application. The advantages and limitations of this technique are also discussed