The comparison of estimation methods on the parameter estimates and fit indices in SEM model under 7-point Likert scale
AbstractIn this article, the author discusses the issues and problems associated with the influence of different estimation methods on the level of obtained parameters and goodness-of-fit of a Structural Equation Model (SEM) in the context of data measured on a 7-point Likert scale. Thus, the objective of the conducted analysis was to compare the selected methods of estimation such as maximum likelihood (ML), maximum likelihood mean adjusted (MLM), maximum likelihood mean-variance adjusted (MLMV), weighted least squares (WLS), weighted least squares mean adjusted (WLSM) and weighted least squares mean-variance adjusted (WLSMV) on the basis of respective parameter statistics, for which the quality of the SEM model fit was assessed. Eventually, among the presented methods, the best estimation procedure was selected. The area of empirical study and the subject of investigation refers to the opinion of consumers about the unethical behavior of companies in the area of marketing.
|Journal series||Archives of Data Science, Series A, ISSN 2363-9881, (0 pkt)|
|Publication size in sheets||0.75|
|Keywords in English||Estimation methods, Structural Equation Models, 7-point Likert scale, fit indices|
|Score||= 5.0, 17-03-2020, ArticleFromJournal|
|Citation count*||5 (2020-05-30)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.