Preface

The \(\texttt{R}\) software has become popular among researchers due to its flexibility and open-source nature. However, researchers in the fields of public health and epidemiology are more accustomed to commercial statistical software such as \(\texttt{SAS}\), \(\texttt{SPSS}\) and \(\texttt{Stata}\). This paper provides a Comprehensive comparison of analysis of health survey data using the \(\texttt{R}\) \(\texttt{survey}\) package, \(\texttt{SAS}\), \(\texttt{SPSS}\) and \(\texttt{Stata}\). We provide detailed \(\texttt{R}\) codes and procedures for other software packages on commonly encountered statistical analyses, such as estimation of population means and regression analysis, using datasets from the Canadian Longitudinal Study on Aging (CLSA). It is hoped that this work stimulates interest among health science researchers to carry out data analysis using \(\texttt{R}\) and also serves as a guide for statistical analysis using different software packages.