VIF. # now check for multicollinearity check_collinearity(model) ## # Check for Multicollinearity ## ## Low Correlation ## ## Parameter VIF Increased SE ## gear 1.53 1.24 ## ## Moderate Correlation ## ## Parameter VIF Increased SE ## wt 5.05 2.25 ## cyl 5.41 2.33 ## disp 9.97...
theglmwere applied using a Poisson regression (Poisson error structure). However, evaluation of Poissonglmis based on the assumption that the dispersion parameter is equal to 1. The model is inadequate
There were also no signs of extreme multicollinearity as indicated by the Variance Inflation Factor (VIF) (VIF < 1.97) and tolerance (tolerance > 0.50) levels for each construct (Hair et al., 1998). Table 2. Correlations. ConstructsCorrelations & square root of average variance extracted ...
For multiple linear regression, judgingmulticollinearityis also critical from the statistical inference point of view. This assumption assumes minimal or no linear dependence between the predicting variables. Outlierscan also be an issue impacting the model quality by having a disproportionate influence on...