Composite Rank Index Method for Stratified Random Sampling in Social Science Research: A Micro-Level Case Study - Kumar, Ashutosh; Sharma, P.R. (National Geographical Journal of India, 2022)
In social science research, it is important to frame a sample design which is least biased to collect primary data in the field adopting Stratified Random Sampling which is very much appropriate for the classification and derive certain findings and results. However, in this sampling type, the method of stratification is a matter of confusion among the researchers. Methods adopted by the past researchers are not the same, rather they are less statistical. This confusion led me to try a fresh method in this regard for my research work. Further, I have gone through a ‘Six-Steps Method’ to determine different strata of Sample Units (followed by the Sample Size and Respondents Design) which is, perhaps, more appropriate for statistical analysis, scientific in nature than any other method of Stratified Random Sampling. The theme and area of the study for present case study is ‘An Appraisal of Rural Development Programmes in Raghopur Block, District Supaul of Bihar’. The present paper is nothing but the illustration of this new method based on the ‘Composite Rank Index’. If it is relevant, this study can also be used by others for determining the sample based on the requirements of their research objectives.