Abstract

Basic methods and techniques involved in the determination of minimum sample size at the use of Structural Equation Modeling (SEM) in a research project, is one of the crucial problems faced by researchers since there were some controversy among scholars regarding methods and rule-of-thumbs involved in the determination of minimum sample size when applying Structural Equation Modeling (SEM). Therefore, this paper attempts to make a review of the methods and rule-of-thumbs involved in the determination of sample size at the use of SEM in order to identify more suitable methods. The paper collected research articles related to the sample size determination for SEM and review the methods and rules-of-thumb employed by different scholars. The study found that a large number of methods and rules-of-thumb have been employed by different scholars. The paper evaluated the surface mechanism and rules-of-thumb of more than twelve previous methods that contained their own advantages and limitations. Finally, the study identified two methods that are more suitable in methodologically and technically which have identified by non-robust scholars who deeply addressed all the aspects of the techniques in the determination of minimum sample size for SEM analysis and thus, the prepare recommends these two methods to rectify the issue of the determination of minimum sample size when using SEM in a research project.

Highlights

  • The Structural Equation Model (SEM) is one of the most extensively used quantitative multivariate data analysis technique which is currently employing to examine the relationship between observed and latent variables of the exploratory, and confirmatory hypothesis testing approaches as well as various types of predictive analysis models. This modeling technique is suitable in the social sciences where mostly the key concepts are not openly observable and are inherently latent generally defined as latent variables (Kline, 1998; Kock & Lynn, 2012)

  • Monte Carlo simulation has been employed as a method of determining the minimum sample size of the PLS-SME (Kock, 2016; Paxton et al, 2001; Robert & Casella, 1999; Wolf et al, 2013)

  • The above review of the selection of minimum sample size determination in the prior literature has provided more than twelve methods that have been employed by the past researchers

Read more

Summary

Introduction

The Structural Equation Model (SEM) is one of the most extensively used quantitative multivariate data analysis technique which is currently employing to examine the relationship between observed and latent variables of the exploratory, and confirmatory hypothesis testing approaches as well as various types of predictive analysis models. SEM has greater flexibility on its nature because it can be used to examine very complex relationships among a variety of data types such as dimensional, categorical censored or count as well can be used to compare among the alternative models (Schreiber, Nora, Stage, Barlow, & King, 2006; Wolf, Harrington, Clark, & Miller, 2013) Inside of this flexibility of the SEM, it has been identified an anomaly, which is the unavailability of comprehensive guidelines regarding the sample size requirements by the past researchers.

Objectives
Methods
Findings
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call