What is linear binomial regression and how it differs from binomial regression?

Binomial regression is a general term where the dependent variable is binomial. Typically this is conducted by generalized linear model.

The two common types are logistic regression and probit regression, where logit and probit are the link functions applied, respectively.

I'm not familiar with the term "linear binomial regression". My guess is that it is referring to what this Wikipedia article calls a "linear probability model" : https://en.wikipedia.org/wiki/Linear_probability_model . If so, it is usually better to use logistic or probit regression.

However, this term might just mean something more general, like "generalized linear regression" as opposed to a discrete choice model or other approach.

For SPSS:

https://stats.idre.ucla.edu/spss/dae/probit-regression/

https://stats.idre.ucla.edu/spss/dae/logit-regression/

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