Structural equation modeling applied to proposed statistics attitudes-outcomes model: a case of North-West University statistics students
Ncube, Andrew Bokang
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The purpose of this study was to investigate the structural relationships among students’ self-reported statistics anxiety, their attitudes toward statistics, and statistics outcomes by testing the proposed statistics attitudes-outcomes model. This study utilized a survey research design, SEM and PLS methodologies. The participants of the current study consisted of 583 first-year undergraduate students enrolled in statistics courses in a university in South Africa. There were 49 variables altogether. The participants were from different programmes within the Commerce Faculty. The modified versions of the Survey of Attitudes toward Statistics- 36 and MPSP were used to collect data. The modified SATS-36 and MPSP served to confirm the factor structure of components of statistics attitudes including self-efficacy, anxiety and statistics outcome. Confirmatory factor analysis results revealed that five of the nine factors were unreliable and thus invalid, using Cronbach’s alpha measure of item consistency. The best model, after modification had higher model fit indices. This model used 448 observations; and the chi-square (< 0.0001) was significant implying bad fit perhaps due to many variables and large sample size used. The root mean square error of approximation (= 0.0491) is less than the cut-off criterion on 0.5 implying good fit. The probability of close fit (=0.6648) showed an improvement after variable and case deletion. The comparative fit index (=0.8792) was steadily on the increase due to the deletion of variables and cases, as well. The overall model had acceptable fit. With indices very close to the 0.90 cut off criterion. In contrast, exploratory factor analysis revealed that all but two of the constructs, had good to excellent reliability and eight variables been consequently deleted due to them being below the cut-off criterion. All other indicators had a significant loading into a construct. All indicators of the final factor structure were found to be significantly loading into their factors after performing EFA. Structural equation modeling was used to test the hypothesised structural equation model. Partial least squares analysis reliability results are consistent with those of structural equation modeling, with only two constructs in both valid. The contradictory chi-square results and increasing fit indices suggests that the number of cases and variables has an impact on the overall fit of the model.