Revolutionizing Developmental Research: New Model for Longitudinal Data Analysis
The article discusses using a general linear mixed model to analyze data in developmental research. This model is helpful for studying growth over time, even when data intervals are irregular or some data points are missing. By properly modeling the covariance structure, researchers can accurately estimate model parameters. This approach is more effective than traditional methods for analyzing longitudinal data, allowing for a precise understanding of how variables change over time.