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cheapbag214s
Posted: Mon 18:46, 02 Sep 2013
Post subject: Extracting meaningful information from a logistic
Extracting meaningful information from a logistic regression model,
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Let's say that I model whether I wear red shoes depending on the weather. Red shoes,
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, which is my dependent variable,
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, 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,
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, 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,
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, 30% when mild,
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, 40% when warm,
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, and so forth.
I'm wondering if modeling is a requirement for finding this information,
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?
If so,
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, 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,
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. The type "response" gives you probabilities rather than logits,
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.
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