Statistics Regression Analysis Statistics
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very clear, very concise and VERY helpful!
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@heatherakapeanut I don't understand your question or observation?
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hmmm....let me revise that. if the DV was binary (dichotomous)? (e.g., yes,no) for hair loss, then it would be suitable for logistic regression? then you could add in other variables that might also account for the effects?
i'm sorry to be a bother! :)
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can you provide an example of how logistic regression might be used with the hair loss due to age example? :) if the DV (hair loss) was measured by none, some, or all, would that work? :) i think i just confused myself. anyway, thanks for the vids!
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helpful video, thank you.
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Wonderfully explained!
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Could you say in the last example that the relationship between hair loss and age is non-linear, instead of breaking down the age in blocks?
Jdonovanford 1 year ago
@Jdonovanford Good point. Yes you could say it was non linear. There are two problems with non linear. The first is the math is very hard to create anything other than a linear relationship. The second is often there is a "step function" or "tipping point." Let's say that some men may not lose any hair until age 30. Measured R squared may be zero up to that point. Nonetheless, good observation.
statisticsfun in reply to Jdonovanford (Show the comment) 1 year ago