Re: st: Sample size for maximum likelihood estimates

[Richard Williams <richardwilliams.ndu@gmail.com>]

At 10:57 AM 8/11/2011, Maarten Buis wrote:
> On Thu, Aug 11, 2011 at 5:20 PM, dk wrote:
> > Take example If, my dependent variable is respondent go for purchasing
> > x product or not. I have response 60 % purchase and 40 % do not
> > purchase. Then is it possible to use 20 explanatory variables.
>
> That still depends on the distribution of your explanatory variables
> (low variance means less power which means more observations are
> needed), the correlations between these variables (higher correlations
> means less power which means more observations are needed) and whether
> or not these include interaction terms (interaction terms mean less
> power which means more observations are needed). I am sorry, there
> really is no generic answer to your question.
>
> -- Maarten
Some of the suggestions that Scott Long has tossed out are summarized 
on pp. 3-4 of
http://www.nd.edu/~rwilliam/stats3/L02.pdf

As Maarten says, there doesn't seem to be any nice simple formula for 
deciding what the right sample size is. But it does seem like you 
need a larger sample for a logit or probit analyses than you would 
for an OLS regression.

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Richard Williams, Notre Dame Dept of Sociology
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