Essentials of Political Research 2018
DOI: 10.4324/9780429500749-17
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Cited by 9 publications
(5 citation statements)
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“…Hence, all the independent variables (TA, Age, OC, HRC and ROA) have the eligibility to be retained and included in the same regression model. The strength of correlation confirms that that there is no multicollinearity problem as the results indicate that correlation is less than the cut-off value of 0.7 (Monroe, 2020;Mubaraq & Ahmed Haji, 2014).…”
Section: Resultssupporting
confidence: 58%
“…Hence, all the independent variables (TA, Age, OC, HRC and ROA) have the eligibility to be retained and included in the same regression model. The strength of correlation confirms that that there is no multicollinearity problem as the results indicate that correlation is less than the cut-off value of 0.7 (Monroe, 2020;Mubaraq & Ahmed Haji, 2014).…”
Section: Resultssupporting
confidence: 58%
“…A PCA, with Oblimin rotation of the criteria, resulted in 3 components, explaining 60.012% of the total variance, with the KMO value = 0.929 and p < 0.001 for Bartlett's test. Variables with factor loadings above 0.4 were kept, which Tabachnick and Fidell (2007) have suggested is an acceptable rule. Park infrastructure and tourism service were the most important components, each accounting for approximately 24% of the variance, and the natural characteristics component explained about 12% of the variance ( Table 5 ).…”
Section: Resultsmentioning
confidence: 99%
“…To assess unidimensionality and minimise measuring bias, we used goodness-of-fit indices like; χ 2 /df, goodness-of-fit index (GFI), comparative fit index (CFI) and root mean square error of approximation (RMSEA). The model fit indices for the model were within the suggested threshold values ( χ 2 /df = 1.98, GFI = 0.92, CFI = 0.96, TLI = 0.95, RMSEA = 0.04) (Tabachnick and Fidell, 2007).…”
Section: Resultsmentioning
confidence: 80%