Hello everyone

I am having trouble interpreting some of my results.

I am using logistic regression to infer a model based on measured data. Some of my explanatory variables are continuous (e.g. temperature [°C]) and some are categorical (e.g. time of day [night, morning, day, afternoon, evening]). To investigate multicollinearity issues, I have calculated Generalized Variance Inflation Factors (GVIF) in R (using the CAR package). R automatically calculates GVIF^(1/(2Df)), which to my understanding is an estimate of the factor by which the confidence interval of each coefficient is inflated (please correct me if I am wrong).

My problem is: How should I interpret the GVIF of interaction terms between continuous and categorical variables?

One of my simple models looks like this:

with the following GVIFs

I would like to make a table like the one below:

My problem is: How do I calculate the Inflation of the confidence intervals?

I would really appreciate if anyone can help!!

I am having trouble interpreting some of my results.

I am using logistic regression to infer a model based on measured data. Some of my explanatory variables are continuous (e.g. temperature [°C]) and some are categorical (e.g. time of day [night, morning, day, afternoon, evening]). To investigate multicollinearity issues, I have calculated Generalized Variance Inflation Factors (GVIF) in R (using the CAR package). R automatically calculates GVIF^(1/(2Df)), which to my understanding is an estimate of the factor by which the confidence interval of each coefficient is inflated (please correct me if I am wrong).

My problem is: How should I interpret the GVIF of interaction terms between continuous and categorical variables?

One of my simple models looks like this:

Code:

```
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -8.76208 2.54158 -3.447 0.000566 ***
Temperature 0.08847 0.11441 0.773 0.439363
timeMorning 3.20504 2.82524 1.134 0.256614
timeDay 0.72913 2.77043 0.263 0.792409
timeAfternoon -0.34141 2.77430 -0.123 0.902057
timeEvening -0.97397 3.16012 -0.308 0.757926
Temperature:timeMorning -0.02669 0.12782 -0.209 0.834601
Temperature:timeDay 0.06239 0.12415 0.503 0.615302
Temperature:timeAfternoon 0.09116 0.12386 0.736 0.461711
Temperature:timeEvening 0.06535 0.13907 0.470 0.638410
```

Code:

```
GVIF Df GVIF^(1/(2*Df))
Temperature 2.091206e+01 1 4.572971
time 1.595779e+08 4 10.601604
Temperature:time 1.899285e+08 4 10.834872
```

Code:

```
Estimate std.Dev std.Err C.I. 2.5% C.I 97.5% Inflation
Intercept
Night -8.76208 2.54158 0.010494 -8.78 -8.74 XX
Morning -5.55704 3.800212 0.01569 -5.59 -5.53 XX
Day -8.03295 3.759642 0.015523 -8.06 -8.00 XX
Afternoon -9.10349 3.762495 0.015535 -9.13 -9.07
Evening -9.73605 4.055365 0.016744 -9.77 -9.70
Temperature
Night 0.08847 0.11441 0.000472 0.0875 0.0894
Morning 0.06178 0.171545 0.000708 0.0604 0.0632
Day 0.15086 0.168828 0.000697 0.1495 0.1522
Afternoon 0.17963 0.168615 0.000696 0.1783 0.1810
Evening 0.15382 0.180084 0.000744 0.1524 0.1553
```

I would really appreciate if anyone can help!!

Last edited: