Hi, welcome to Just Answer. Here it is.
1. DV and error terms don't have to be normally distributed,
2. DV doesn't have to have equal variance in each group
2. No linear relationship between the IV and DV has to be assumed.
3. Can handle nonlinear effect, interaction effect and power terms
4. IV can be categorical variable and bounded.
Disadvantage: requires large sample size to achieve stable results.
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Is your answer referring to logistic regression, sequential logistic regression, or stepwise logistic regression??
My question asks for the advantages and disadvantages of all three. I am not sure what you are answering.
Also, what criteria would be used to decide which method to use?
Sorry I thought you asked the pros and cons of logistic regression in general. I assume "logistic regression" means using all predictors. Please let me know if otherwise.
Pros: use all predictors, will not miss important ones.
Cons: may have multicollinearity .
Stepwise logistic regression
Pros: can find a model that is parsimonious and accurate. Maybe able to find relationships that have not been tested before.
Cons: may over fit the data.
Sequential logistic regression
Pros: can test the relationship that the research is interested. Maybe able to find relationships that have not been tested before.
Cons: may miss the chance to find important relationship.
Please let me know if you have any questions and accept. Thanks.