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| | Statistical Modeling, Causal Inference, and Social Science: April 2005 Archives |
 | | The next generalization, modeling missing data or, more generally, the process of data collection, generalizes the likelihood from p(ytheta) to p(y,Itheta,phi), where I represents the information of which data points are actually observed, and phi are parameters describing the design of the data-collection and recording process (Rubin, 1976). |
 | | In general, more complex models are better (see here, also with some interesting discussion), but a simpler model is less effort to set up and can be used as a starting point in a wide range of examples. |
 | | In general, I'm more in favor of students collecting their own data rather than using the web (see Section 11.4 of our book) but here they have to do a little work, what with the sampling and the content evaluation, so it seems that it could be reasonable. |
| www.stat.columbia.edu /~cook/movabletype/archives/2005/04 (11119 words) |
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