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Complex Samples Ordinal Regression
Each term in the model is tested for whether its effect equals 0. Terms with significance values less than 0.05 have some discernable effect. Thus, agecat and drivefreq contribute to the model, while the other main effects do not. In a further analysis of the data, you would consider removing gender and votelast from the model.
Parameter Estimates
The parameter estimates table summarizes the effect of each predictor. While interpretation of the coefficients in this model is difficult due to the nature of the link function, the signs of the coefficients for covariates and relative values of the coefficients for factor levels can give important insights into the effects of the predictors in the model.
For covariates, positive (negative) coefficients indicate positive (inverse) relationships between predictors and outcome. An increasing value of a covariate with a positive coefficient corresponds to an increasing probability of being in one of the “higher” cumulative outcome categories.
For factors, a factor level with a greater coefficient indicates a greater probability of being in one of the “higher” cumulative outcome categories. The sign of a coefficient for a factor level is dependent upon that factor level’s effect relative to the reference category.
Figure
Parameter estimates
You can make the following interpretations based on the parameter estimates:
Those in lower age categories show greater support for the bill than those in the highest age category.
