For example, that "multivariate regression" pertains to multiple dependent variables and a single dependent variable? I'm trying to make sense of the term "multivariate multiple regression" …

Sample size calculation for logistic regression is a complex problem, but based on the work of Peduzzi et al. (1996) the following guideline for a minimum number of cases to include in your …

But there appears to be very little documentation on multiple logistic regression models like my situation. I don't know how to do a more detailed power analysis for multiple logistic regression.

Communicating complex information: the interpretation of statistical interaction in multiple logistic regression analysis. American journal of public health, 93 (9), 1376-1377.

Multinomial Logistic regression is the extension of binary logit regression. It is used when the dependent variables of the study is three and above, whereas, binary logit is used when the …

Multiple regression asks a different question from simple regression. In particular, multiple regression (in this case, multiple logistic regression) asks about the relationship between the …

Is it possible to conduct a regression if all dependent and independent variables are categorical variables?

That seems a bit incorrect as there really should be a multiple comparison check no? Is it really fair to say something like $\beta_1$ and $\beta_2$ are significant but $\beta_3$, $\beta_4$ …

Are there any alternatives to using the multinomial logistic regression when handling such unordered categorical outcomes? When dealing with binary dependent variables there seems …

However, ordinal logistic regression can also be hierarchical and multiple: Those terms refer to the number of independent variables and how they are entered into the regression. "Multiple" …