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From |
"Austin Nichols" <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Chi-square test for differences in a binary outcome |

Date |
Wed, 4 Jul 2007 13:53:12 -0400 |

Christoph Vanberg <cvanberg@gmail.com>: It's not a nonparametric test, but -clogit- should be applicable here. See http://www.stata.com/statalist/archive/2007-07/msg00125.html for some recent discussion of -clogit-. On 7/4/07, Christoph Vanberg <cvanberg@gmail.com> wrote:

Hello, I want to test for an effect of a randomly administered treatment on a binary variable y=0 or 1. My data consists of observations on the same set of individuals in different conditions, thus the samples are not independent. Specifically, three treatment conditions are applied to each individual a random number of times. I want to compare outcomes between subjects in two of these three conditions. Since the number of times an individual is in these two conditions is random, it is not balanced across subjects. I am looking at data of the following form, where the fractions represent (times y=1 is observed in condition x) / (times subject is in condition x). i: 1 2 3 4 .... N x1: 1/2 1/1 1/1 2/3 .... 3/3 x2: 0/1 0/0 1/2 1/2 .... 1/4 As I understand it, McNemar's Chi-square test (mcc in Stata) tests for treatment effects if you have paired observations, each with one outcome. That is, it applies to the following type of data, where i identifies matched pairs, x1 is a dummy indicating y=1 in condition 1 and x2 is a dummy indicating y=1 in condition 2. i: 1 2 3 4 .... N x1: 1 1 1 0 .... 1 x2: 0 0 1 1 .... 0 This is pretty close to what I want to do, but the test does not apply to my situation, where the same individual can be repeatedly observed in the same condition. Does anyone have a suggestion as to what type of nonparametric test might be appropriate in such a case?

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**References**:**st: Chi-square test for differences in a binary outcome***From:*"Christoph Vanberg" <cvanberg@gmail.com>

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