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Re: st: RE: Pearson chi square and Rao and Scott correction validity

From   Steven Samuels <>
Subject   Re: st: RE: Pearson chi square and Rao and Scott correction validity
Date   Thu, 6 Nov 2008 17:04:00 -0500

I've looked though Chapters 6-7 of Chamber's and Skinner's book Analysis of Survey Data, Wiley, 2003, but I have no definitive answer. I do have some thoughts:

* "Expected" count is not a guide in the survey setting--it is a sum of weights of sample observations in the table cell.

* The accuracy of the second-order Rao-Scott statistic chi square, probably the best test in -svy: tab-, is apt to depend on the number of clusters, on the crude counts, and on the distribution of the observations across clusters. The rule of thumb of 5 observations (or 1) in a cell is based on theory of i.i.d. observations that does not hold in the complex survey setting.

* With a small number of events, I ordinarily display only unweighted numbers and do not reported weighted estimates or confidence intervals. When I have wanted to infer something about a proportion based on small outcome count, I've resorted to the methods on pp. 64-68 of Korn and Graubard (1999) Analysis of Health Surveys, Wiley.

A quick Google search turned up one survey which would not report a cell with fewer than 25 observations ( showsrvy.cfm?srvy_CatID=5&srvy_Seri=16) and another in which the minimum cell size was 4,000! ( cdic-mcc/17-3/a_e.html).

So a guess for Ángel is that not even five observations in table cell is enough.


On Nov 6, 2008, at 7:33 AM, Nick Cox wrote:

There is no need to invoke belief! My -tabchi- and -tabchii- (programs) from the -tab_chi- package on SSC do indeed give warnings. (There is no Stata program called tab-chi.)

But these old warnings are very conservative. Many writers now advise that chi-square works fine so long as all expected frequencies are above about 1. In any case, the point can be explored by simulations or bootstrapping. Often it is better to use Fisher's exact test.

I can't advise on the main issue, which is for svy-savvy people, but in general very low expected frequencies could be problematic for any method.


Ángel Rodríguez Laso

I've been reviewing the manuals and statalist archives and I've
confirmed that Stata does not give any automatic warning message when
requirements for a valid chi-square test are not met (i.e. no more
than 20% of the expected values in a table are less than 5 and none
are less than 1), what I think is a nuisance. I suppose this can be
only worked out by writing the option 'expected' after tabulate and
checking oneself if the requirements are met. I believe Cox's tab-chi
package does give a warning when requirements are not met.

I wonder also if the Rao and Scott correction of Pearson chi-square
that is recommended for survey designs needs the same requirements.
The problem then would be that -svy:tab- doesn't support the
'expected' option neither tab-chi is suitable for survey analysis.

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