Sample selection in social science research: A holistic approach to methodological rigor

Abstract

The present study investigates the crucial elements of sample selection in social science research, thoroughly examining the nuances of sampling techniques, categories, and factors. The paper offers a thorough overview of the procedures involved in sampling strategies, with a particular emphasis on non-probability and probability approaches. It also discusses the critical role that sample size determination plays, taking into account variables like cost, ethics, statistical power, accuracy, and generalizability in addition to type I and type II errors. The paper also closely examines how several elements, such as research objectives, design, analytical instruments, and resource constraints, affect the choice of the ideal sample size. The topic of choosing the right data analysis software and how it affects choices about sample size is covered in detail. In the last section of the study, the ideas of power, effect size, and minimum sample size in statistical analysis are thoroughly explored, with a focus on partial least squares structural equation modelling (PLS-SEM).