If a test-statistics is expressed in z-values (instead of, for example, t-values), would it be appropriate to use those values for some further inferences? For example, to average a pair and another pair, to compare the difference between them and so on. As the values are standard normal this should be fine. However, are there some covert traps?
This would be a simple example - a logistic regression summary table:
GENDER HEIGHT CONDITION Estimate Std. Error z value
female short A 2.1351 0.2517 8.481
female short B 1.3336 0.2336 5.710
female tall A 1.9229 0.2521 7.627
female tall B 1.4435 0.2364 6.105
male short A 0.6710 0.2142 3.132
male short B 0.8949 0.2184 4.098
male tall A 0.4108 0.2135 1.924
male tall B 1.2879 0.2206 5.839
So, if one would wish to compare short and tall females, or short females and males, would it work to take the average of z-values?