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Extracting meaningful information from a logistic regression model,[link widoczny dla zalogowanych]
Let's say that I model whether I wear red shoes depending on the weather. Red shoes,[link widoczny dla zalogowanych], which is my dependent variable,[link widoczny dla zalogowanych], is a dichotomous variable as I either wear them or don't. Weather is a variable with five 'levels' and I'm trying to find the probability that I will wear read shoes.
Let's say I model out this relationship with a logistic regression model in R:
Now,[link widoczny dla zalogowanych], what I am interested in is finding what are the probabilities for wearing red shoes for each of the five 'levels' in weather. So perhaps I might have a 20% probability of wearing red shoes when cold,[link widoczny dla zalogowanych], 30% when mild,[link widoczny dla zalogowanych], 40% when warm,[link widoczny dla zalogowanych], and so forth.
I'm wondering if modeling is a requirement for finding this information,[link widoczny dla zalogowanych]?
If so,[link widoczny dla zalogowanych], how does one go from somewhat meaningful regression coefficients to meaningful probabilities in R?
All you need to do is supply a new data frame to R with the values that you want to use for the independent variables as above,[link widoczny dla zalogowanych]. The type "response" gives you probabilities rather than logits,[link widoczny dla zalogowanych].
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