Simple logistic and poisson regression questions

[Sebastian Umana]

Hello, this might be a common question but I need to know what to do in order to continue with the analyses I am doing. I am currently doing a logistic and Poisson regression models with multiple predictors, after multiple steps, I ended with only one significant predictor for both models. My question is, is it necessary to do a goodness of fit test, I already did and it was significant but I am not sure if this is the right call.

Se below the stata imput for the logistic regression.

logit Mannheimiaspp i.Howoftendoyoudisinfectorcl

Iteration 0: log likelihood = -55.226563
Iteration 1: log likelihood = -52.259461
Iteration 2: log likelihood = -52.256889
Iteration 3: log likelihood = -52.256889

Logistic regression Number of obs = 80
LR chi2(1) = 5.94
Prob > chi2 = 0.0148
Log likelihood = -52.256889 Pseudo R2 = 0.0538

----------------------------------------------------------------------------------------------
Mannheimiaspp | Coefficient Std. err. z P>|z| [95% conf. interval]
-----------------------------+----------------------------------------------------------------
2.Howoftendoyoudisinfectorcl | -1.254617 .5317482 -2.36 0.018 -2.296824 -.2124092
_cons | .4924765 .2706147 1.82 0.069 -.0379186 1.022872
----------------------------------------------------------------------------------------------

. estat gof

Goodness-of-fit test after logistic model
Variable: Mannheimiaspp

Number of observations = 80
Number of covariate patterns = 2
Pearson chi2(0) = 0.00
Prob > chi2 = .

Thank you very much!

[Carlo Lazzaro]

Sebastian:
welcome to this forum.
I'm sorry to disappoint you, but the result of -estat gof- do not show any evidence of statistical significance.
As your only predictor is a categorical variable, the test cannot be performed.
Setting this issue aside for a while, it is very diffiult to believe that a simple regression (that is, a regression with one predictor only) can be considered informative by any decent reviewer/supervisor/discussant.