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Data with categorical values that can be ordered by magnitude, but the exact distance (spacing) between categories is undefined or unknown.

5 votes
2 answers
2k views

Interpreting coefficients of ordinal independent variables in logistic regression in R

I have conducted a logistic regression in R > Model <- glm(A ~ B + C, family = "binomial", data = Data) > summary(Model) Coefficients: Estimate Std. Error z value Pr(>|z|) (Inte …
2 votes
2 answers
464 views

How to interpret insignificant intercept in logistic regression with orthogonal polynomial e...

I have conducted a logistic regression. Model <- logistf(A ~ C, family ="binomial"(link = "logit"), data=Data) The dependent variable is binary (1,0) The sole independent variable is ordinal with 3 l …
0 votes
0 answers
136 views

Plotting probabilities from firth's logistic regression with ordinal predictor in R

I have fit a model using firth's logistic regression. library(logistf) Model <- logistf(a~b, data = data) Where b is an ordinal variable with 3 levels. Therefore the summary of the model looks like …
1 vote
1 answer
664 views

VIF scores for ordinal independent variables

I suspected there was a high degree of multicollinearity in the independent variables of my data. Each of these variables is ordinal. The original model is library(logistf) EC_all <- logistf(Erad_cont …
3 votes
1 answer
2k views

Testing multi-collinearity of ordinal independent variables in R

I am trying to conduct an ordinal logistic regression, but I first want to test if I fulfill the assumption of no multicollinearity. All of my 8 independent variables are ordinal with up to 5 levels. …
2 votes
1 answer
70 views

Comparing the predictive power of two non-independent ordinal independent variables

I am looking to compare the predictive power of two ordinal independent variables (RA & 0.5RA+0.5RM) on success (please see image). These independent variables are not independent of each other.(C …