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Hello! I am new to research and I want to see if this makes sense. I have a dichotomous dependent variable (i.e., vaccination status) and a categorical independent/predictor variable (vaccine hesitancy). The categories for vaccine hesitancy are yes (i.e., vaccine hesitant) and no (i.e., vaccine hesitant). In completing a automatic recode for my independent variables, they become numeric. From there, is it okay to run a regression? If so, does it matter if I run a linear or logistic regression? Similarly, I am doing the same thing for multiple predictors/independent variables (i.e., social need; housing, employment, childcare, economic stability, etc.) with vaccination status (dependent/dichotomous). I manipulated the independent variables to denote need (so "yes" for any need endorsed and "no" for lack of need). So, if someone endorses a need for employment then "yes" was recoded to a numeric value, for example. Am I now able to run a linear or logistic regression?
Hi @ashley craft Yes.
Here are the pages in our documentation covering Logistic Regression
Thank you. I took a look and it leaves me with another question. Do I need to run something else before the logistic regression such as a Chi Square? If so, why is that?
I did not see this in the "logistic regression" link above. Are you familiar with what this may mean? Is my analysis invalid?