Design-based versus Model-based Methods: a Comparative Study Using Longitudinal Survey Data

Survey data analysis using complex sampling designs ought to account for clustering, stratification and unequal probability of selection. Design-based and model-based methods are two commonly used routes taken to account for such survey designs. Several studies of cross-sectional survey designs have shown that these two approaches provide similar results when the model fits the data well. The present paper aims at comparing these two approaches using the longitudinal National Population Health Survey (NPHS) dataset. The NPHS is an ongoing longitudinal study, for which data collection was based on a stratified multistage sampling design. A marginal modeling approach proposed by Rao (1998) was used by way of a design-based method. The Generalized Estimating Equation (GEE) method, proposed by Liang and Zeger (1986), was used as a typical model-based approach. Results obtained from these methods were compared.