I have a list of observations of females and their responses, categorized into 5 behaviors, to a potential threat. I'm wondering if, for each response type, whether the presence of an infant makes it more or less likely a female would perform that response. (E.g., we might hypothesize that females with infants are more likely to hide and less likely to go looking for food.)
The following was suggested:
- Bin females by social group (i.e., each bin would only contain females who associated with each other).
- Calculate the proportion of each response type observed in each group (all these, for each group, would add to 1).
- Arcsine-transform the proportion data.
- Perform a t-test, for each behavior, to see whether the proportions of females responding that way differs depending on the presence of an infant.
This sounded sketchy to me, and it seems that others agree. The consensus seems to be that, in such cases, it's better to use multinomial regression (in this case, BEHAVIOR ~ INFANT_STATUS) to determine whether infant presence has an effect. However, I was wondering whether I could use those results determine whether (and in what direction) the presence of an infant affects the probability of each response behavior. Also, would that be possible if I were to include additional independent variables?
Any advice you can give, on analytical design or actual coding, is much appreciated. I've been doing this in R, but I'm more comfortable in MATLAB if that works as well. Thanks in advance.