An Approximate Test for Homogeneity of Correlated Correlation Coefficients
dc.contributor.author | Raghunathan, Trivellore E. | en_US |
dc.date.accessioned | 2006-09-08T21:34:20Z | |
dc.date.available | 2006-09-08T21:34:20Z | |
dc.date.issued | 2003-03 | en_US |
dc.identifier.citation | Raghunathan, Trivellore; (2003). "An Approximate Test for Homogeneity of Correlated Correlation Coefficients." Quality and Quantity 37(1): 99-110. <http://hdl.handle.net/2027.42/43560> | en_US |
dc.identifier.issn | 0033-5177 | en_US |
dc.identifier.issn | 1573-7845 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/43560 | |
dc.description.abstract | This paper develops and evaluates an approximate procedure for testing homogeneity of an arbitrary subset of correlation coefficients among variables measured on the same set of individuals. The sample may have some missing data. The simple test statistic is a multiple of the variance of Fisher r-to-z transformed correlation coefficients relevant to the null hypothesis being tested and is referred to a chi-square distribution. The use of this test is illustrated through several examples. Given the approximate nature of the test statistics, the procedure was evaluated using a simulation study. The accuracy in terms of the nominal and the actual significance levels of this test for several null hypotheses of interest were evaluated. | en_US |
dc.format.extent | 83393 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Kluwer Academic Publishers; Springer Science+Business Media | en_US |
dc.subject.other | Social Sciences, General | en_US |
dc.subject.other | Chisquare Test | en_US |
dc.subject.other | Fisher R-to-Z | en_US |
dc.subject.other | Missing Data | en_US |
dc.subject.other | Methodology of the Social Sciences | en_US |
dc.title | An Approximate Test for Homogeneity of Correlated Correlation Coefficients | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Statistics and Numeric Data | en_US |
dc.subject.hlbsecondlevel | Philosophy | en_US |
dc.subject.hlbsecondlevel | Social Sciences (General) | en_US |
dc.subject.hlbtoplevel | Humanities | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.subject.hlbtoplevel | Social Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | University of Michigan, USA | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/43560/1/11135_2004_Article_394854.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1023/A:1022567712647 | en_US |
dc.identifier.source | Quality and Quantity | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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