This paper demonstrates the importance of panel data analysis that has not yet been employed by several Japanese sociologists. Although we can build a longitudinal type of data from a cross-sectional retrospective survey, it may further reduce the reliability of responses because of incorrect recall and the sample selection bias. Causal inference becomes a significant task for social scientists, and we need to prepare the panel data that includes detailed information about changes in order to resolve this task. While we cannot obtain unbiased estimates from Ordinary Least Squares (OLS) owing to endogeneity, which means that there is a correlation between independent variables and unobserved heterogeneity, we can eliminate the bias from the unobserved heterogeneity if we employ an econometric fixed-effect regression model. In addition, this paper also introduces a hybrid model that applies the idea of group mean centering at multilevel modeling, and it enables us to obtain the within and between estimators simultaneously. Finally, I will introduce the future tasks for panel data analysis.