This paper examines the Longitudinal Aging Study in India (LASI) and its role in providing valuable insights into the health, social, psychological, and economic well-being of the older Indian population. The paper examines the use of dependent independent variables in a multiple linear regression model, tests assumptions of linearity, and examines the significance of the overall model and the individual variables. There are 190 variables in the dataset being used. This paper presents the results of comparing the regression models obtained through basic, forward, and stepwise selection methods where the model obtained using the stepwise selection method, when all the linearity assumptions are satisfied, explains 86.51% of the variation in the dependent variable and the Adjusted R-squared of the model is 0.8374.