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I suspect the culprit here is that some of your observations have variable values that predict success or failure perfectly, but Stata will generally alert you to the fact. Take a peek at the "note" output that Stata produces.
To understand this better, read the Model Identification section of the logit chapter in the pdf manual. This often happens when you ...
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Thanks for posting your data, Carlos. Please bear in mind that I am not an ecologist, so I cannot speak to whether what I propose makes sense in your field. However, given your data, I would suggest you consider a two-level (mixed effects) model, with the 5 yearly observations nested within 30 plots. I would treat sampling site as a fixed factor with three ...
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Comparing two samples of such different sizes, when one sample is large, is actually quite similar to doing a one-sample comparison to a known distribution. To see this, imagine the more extreme case where you are comparing a sample of size $34$ to a sample of size $\infty$. In the latter case, the infinite sample is equivalent to knowledge of the ...
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I think this is "acceptable" but it very much depends on what do you want to do with this figure, and what do you think about the data.
essentially you are doing linear regression with a single explanatory variable, so you should still have 8 degrees of freedom in your size-10 sample, and t-values should be valid.
however, this assumes all the nice ...
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