I have an interesting problem I was hoping someone could offer me some advice with.
I'm currently running binary logistic regression on data (n=62) but in one case (1 dependent, 1 independent both dichotomous) test of the coefficients using the wald chi square test gives a different result than the overall test of the model using the likelihood chi square test.
As the model is significant according to the latter (p=.048) yet the sole independent variable is insignificant according the former (p=.071), I'm not sure which one to run with.
If anyone knows the appropriate course of action, and could let me know, I'd really appreciate it.
The only info I've been able to find is
There are a few other things to note about the output below. The first is that although we have only one predictor variable, the test for the odds ratio does not match with the overall test of the model. This is because the test of the coefficient is a Wald chi-square test, while the test of the overall model is a likelihood ratio chi-square test. While these two types of chi-square tests are asymptotically equivalent, in small samples they can differ, as they do here. Also, we have the unfortunate situation in which the results of the two tests give different conclusions. This does not happen very often. In a situation like this, it is difficult to know what to conclude. One might consider the power, or one might decide if an odds ratio of this magnitude is important from a clinical or practical standpoint.