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Re: st: Use or don't use weights for combined cross-country observations in multi-level model

From   Clive Nicholas <>
Subject   Re: st: Use or don't use weights for combined cross-country observations in multi-level model
Date   Sat, 25 Jun 2011 04:44:49 +0100

Melanie Kolbe wrote:

> after researching different opinions on the topic, I am still at a loss whether I should use weights or not for my model. I am interested whether being in the social group of interest (in comparison to everyone who is not)  affects their response to specific items from the survey I use. My observations are drawn from several EU countries as one country usually does not have enough respondents of the group of interest surveyed and I am also interested in the effects of country-level variables on the responses. So I am not comparing across countries, but just want to run a multi-level model in order to find out whether being in the group of interest affects the response option significantly or not. I use standard control variable such as gender, age, education, political alignment and so on in the regression.
> I have read that for regressions the use of weights can be messy and I am not sure that what I am doing requires weights at all. If anyone could give me a second or third opinion on that I would be grateful.

My only answer to your dilemma is this: just try it.

If your weights don't change your parameter estimates, standard errors
etc that much (and you're confident that your model tells a story
consistent with the theory or theories that you're testing), then the
chances are that you have little to worry about.

So, in short: (1) run the model; (2) ask questions afterwards; (3) see
if you can improve it.

Clive Nicholas

[Please DO NOT mail me personally here, but at
<>. Please respond to contributions I make in
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"My colleagues in the social sciences talk a great deal about
methodology. I prefer to call it style." -- Freeman J. Dyson

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