# Checking assumptions for Logit model hypothesis testing

I have so far used the ordinary least squares (Classical Linear Regression Model) for several projects. There I used to check whether the assumptions such as homoskedasticity, lack of multicollinearity, normality of residuals etc. hold to a satisfactory degree to make sure that the hypothesis tests are valid.

For a new project I am working on, for the first time, I am advised to use the Logit model of the following form--

$$P(Y=1)=f(\beta_0 + \beta_1 X_1 + \beta_2 X_2 + \beta_3 X_1 X_2)$$

$$f(x) = \frac{1}{1+e^{-x}}$$

Here $$Y, X_1$$ and $$X_2$$ are all dummy variables.

I want to test hypotheses of the following form--

$$\beta_1 \neq 0$$ $$\beta_2 \neq 0$$ $$\beta_3 \neq 0$$

How should I go about doing that? And for any method you suggest, I wished to know what are the assumptions that I need to check to make sure the hypothesis tests in this logit regression are valid. Are the assumptions the same as that of CLRM? Any addition or subtraction? Or are the assumptions completely different?

Also, I currently use IBM SPSS mostly, can those assumptions be checked there?

• Can you pleas spell out CLRM? Your model is logistic regression, so see this list of relevant posts. Jul 15, 2020 at 15:50
• By CLRM I meant the Classical Linear Regression Model. I also saw the list you suggested, there are similar questions but what I seek to know is a way to attain p-values for the beta coefficients (assuming the coefficients are 0 as the null hypothesis) and the required assumptions for those p-values to be valid, the answer to which I didn't find there. Jul 15, 2020 at 17:21
• This question is too vague to be answerable yet, because the answer depends on how you test those hypotheses--and there are several different methods in common use. Please indicate that in your edits to the question.
– whuber
Jul 16, 2020 at 13:47
• Added the how part Jul 16, 2020 at 14:12