4.6.5 Exploratory Factor Analysis (EFA)
According to Hair et al. (2010), there are two types of factor analysis, including exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The CFA is a technique for testing the hypothesis about the degree to which the data meet the hypothesised factor. On the other hand, the Exploratory Factor Analysis (EFA) is a data reduction technique (Pallant, 2013). In other words, EFA is a multivariate statistical method to summarisation and data reduction (Hair et al., 2010). The EFA is different with other techniques such as regression and analysis of variance. This technique is an interdependence technique which is not categorised as dependent and independent variables. This study employs SPSS 22 as the software programme to run the exploratory factor analysis. There are some procedures in conducting EFA in this study (Pallant, 2013).
First, this study assesses the suitability of the data for factor analysis. In this step, the n...
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...e hypotheses testing and see the regression weight of the construct’s relationships. However, when the structural model is not fit, there are some ways to improve the model such as using the modification indices and standardised residuals of variance which should be less than 2.58 (Byrne, 2010).
4.6.11 Test of Indirect Relationship
Beside the direct relationship between each variable, this study also examines indirect relationship of some variables. Consequently, to test those relationships this study needs more analysis. According to Baron and Kenny (1986), there are two indirect relationships between variables, including moderating effect and mediating effect. Especially to test the mediating effect of a variable, they argue it can be tested by using the Sobel’s test. Hence, this study uses the Sobel’s test to examine the indirect relationship between variables.
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