Timeline for What is the appropriate glm to estimate data from a numerical rating scale?
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| Apr 13, 2017 at 12:44 | history | edited | CommunityBot |
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| Oct 31, 2016 at 20:55 | vote | accept | hanshansen | ||
| Oct 31, 2016 at 12:15 | comment | added | The Laconic | But again, fractional logit and beta regression are alternatives. For fractional logit, a good short reference is Christopher Baum's "Modeling proportions" in the Stata Journal. Yes, examples are in Stata, but it's a good explanation of the idea anyway. The original paper on the method is Papke, L. E., and J. M. Wooldridge. 1996. Econometric methods for fractional response variables with an application to 401(K) plan participation rates. Journal of Applied Econometrics 11: 619–632. | |
| Oct 31, 2016 at 12:11 | comment | added | The Laconic | Agreed, if you can really take the precision of those measures seriously. If this was a question "how's your overall health on a numeric scale?", then choosing a step size of 1 on a scale of 1-100 is meaningless precision. You might as well bucket into ranges 1-10, 11-20, etc., for example. | |
| Oct 31, 2016 at 6:30 | comment | added | hanshansen | The dependent variable is simply an overall judgement about respondents health, it was collected with a slider ranging between 0 and 100 and stepwidth 1. Most people have something between 70 - 90, so the responses are not really normally distributed. For a ordered logit i feel there are too many possible responses. | |
| Oct 30, 2016 at 0:45 | review | First posts | |||
| Oct 30, 2016 at 0:47 | |||||
| Oct 30, 2016 at 0:42 | history | answered | The Laconic | CC BY-SA 3.0 |