Application of factor analysis to SF-36 quality of life scale

Factor analysis is the process of finding common variables called factors that are thought to have an effect on the correlation or covariance structure between continuous variables. It is divided into exploratory factor analysis and confirmatory factor analysis. In the exploratory factor analysis, factors are determined from the relationships between the variables, whereas in the confirmatory factor analysis, a previously determined hypothesis about the relationship between the variables is tested. In this study, information about factor analysis was given, oblique and orthogonal factor rotation methods were explained and SF-an application on 36 Quality of Life Scale was carried out. While 8 variables were included in the questionnaire conducted with 107 individuals, 8 sub-dimensions were taken in the scale and a total of 16 variables were included in the factor analysis. As a result of the analysis 16 variables were reduced to 5 factors. Five factors, oblique rotation methods; Promax and Direct oblimin methods and Varimax and Quartimax rotation methods were used. The total explained variance of the 5 factors was found to be 73.40%. While 8 dimensions were in the first factor without any rotation, there was a change in the distribution of the dimensions according to the factors after rotation. Similar changes were observed in demographic characteristics. As a result, it was observed that the relationships between demographic characteristics and factors of the 8 sub-dimensions were changed by rotation methods.