Choosing the best type of analysis for my variables and objectives I am struggling to identify the best analysis for my design. My two independent variables are binary (dichotomous) and my dependent variable is also binary (dichotomous). The goal is to find whether there are differences between the IVs in affecting the DV, and whether there is an interaction between my variables. I need what ANOVA does but I cannot use ANOVA as my DV is dichotomous. I'm not sure if a binary logistic regression is a good fit for my aim? I also worry that I may have to use a loglinear model (logit) analysis (I have seen a paper using it for this type of design) as I am struggling to find tutorials of how to conduct the logit type of loglinear analysis in spss.

Binary logistic regression should be fine (basically, ANOVA is linear regression on categorical dummy variables, and what you have is a logistic regression of this kind, at least if model assumptions are OK).
There is no specific distinction between IV and DV in loglinear models, although I think this could probably also be applied here. It would require some thought about what exactly to test, so "out of the box" I'd prefer the logistic regression.
