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Nonparametric Tests for Linkage with Dependent Sib Pairs
Sib pair tests for linkage to a quantitative trait or affection status are examined by simulation. A sibship of size s contributes only s – 1 independent sib pairs but all s(s - 1)/2 pairs are needed for an efficient test. Redundancy increases with sibship size. Using simulated data on the null hypo...
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Published in: | Human heredity 1995-11, Vol.45 (6), p.311-318 |
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container_title | Human heredity |
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creator | Collins, A. Morton, N.E. |
description | Sib pair tests for linkage to a quantitative trait or affection status are examined by simulation. A sibship of size s contributes only s – 1 independent sib pairs but all s(s - 1)/2 pairs are needed for an efficient test. Redundancy increases with sibship size. Using simulated data on the null hypothesis of no linkage, we have considered equal and unequal weights. Unequal weights lose power as measured by the equivalent number of observations, and goodness of fit to the theoretical distribution is degraded. The Fisher z(r) test with equally weighted pairs is more reliable than any t(r) test based on conjectured degrees of freedom, but significance levels must be established by simulation if the number of pairs is small or redundancy is large. An approach to parametric analysis through nuisance parameters is discussed. |
doi_str_mv | 10.1159/000154299 |
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A sibship of size s contributes only s – 1 independent sib pairs but all s(s - 1)/2 pairs are needed for an efficient test. Redundancy increases with sibship size. Using simulated data on the null hypothesis of no linkage, we have considered equal and unequal weights. Unequal weights lose power as measured by the equivalent number of observations, and goodness of fit to the theoretical distribution is degraded. The Fisher z(r) test with equally weighted pairs is more reliable than any t(r) test based on conjectured degrees of freedom, but significance levels must be established by simulation if the number of pairs is small or redundancy is large. 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A sibship of size s contributes only s – 1 independent sib pairs but all s(s - 1)/2 pairs are needed for an efficient test. Redundancy increases with sibship size. Using simulated data on the null hypothesis of no linkage, we have considered equal and unequal weights. Unequal weights lose power as measured by the equivalent number of observations, and goodness of fit to the theoretical distribution is degraded. The Fisher z(r) test with equally weighted pairs is more reliable than any t(r) test based on conjectured degrees of freedom, but significance levels must be established by simulation if the number of pairs is small or redundancy is large. An approach to parametric analysis through nuisance parameters is discussed.</description><subject>Alleles</subject><subject>Biological and medical sciences</subject><subject>Classical genetics, quantitative genetics, hybrids</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Genetic Linkage</subject><subject>Genetics of eukaryotes. Biological and molecular evolution</subject><subject>Humans</subject><subject>Lod Score</subject><subject>Methods, theories and miscellaneous</subject><subject>Models, Genetic</subject><subject>Original Paper</subject><subject>Wills</subject><issn>0001-5652</issn><issn>1423-0062</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1995</creationdate><recordtype>article</recordtype><recordid>eNptkM1Lw0AQxRdRaq0evCsEFMFDdD-z2aPUaoWigvUcNpvZmpomcTdF_O9NSWwvzmWYeT_mDQ-hU4JvCBHqFmNMBKdK7aEh4ZSFGEd0Hw03-1BEgh6iI--X7RhjyQZoEAsmsYyHKH6uylo7vYLG5SaYg298YCsXzPLyUy8g-M6bj-AeaigzKJvgLU-DV507f4wOrC48nPR9hN4fJvPxNJy9PD6N72ahYTFuQhtRRTETWsmYAdaACZWpZYJpK7mhWcqAk0iB0pJpFqWcGao4J0SRNIoZG6Gr7m7tqq91-16yyr2BotAlVGufyE1RKVrwugONq7x3YJPa5SvtfhKCk01KyTallj3vj67TFWRbso-l1S97XXujC-t0aXK_xVikKCWyxc467FO7Bbid4Z_Lxb_ydDrpiKTO7O6XpW-qHcQFwVRhwn4BX2GKOQ</recordid><startdate>19951101</startdate><enddate>19951101</enddate><creator>Collins, A.</creator><creator>Morton, N.E.</creator><general>S. 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Biological and molecular evolution</topic><topic>Humans</topic><topic>Lod Score</topic><topic>Methods, theories and miscellaneous</topic><topic>Models, Genetic</topic><topic>Original Paper</topic><topic>Wills</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Collins, A.</creatorcontrib><creatorcontrib>Morton, N.E.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Human heredity</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Collins, A.</au><au>Morton, N.E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Nonparametric Tests for Linkage with Dependent Sib Pairs</atitle><jtitle>Human heredity</jtitle><addtitle>Hum Hered</addtitle><date>1995-11-01</date><risdate>1995</risdate><volume>45</volume><issue>6</issue><spage>311</spage><epage>318</epage><pages>311-318</pages><issn>0001-5652</issn><eissn>1423-0062</eissn><coden>HUHEAS</coden><abstract>Sib pair tests for linkage to a quantitative trait or affection status are examined by simulation. A sibship of size s contributes only s – 1 independent sib pairs but all s(s - 1)/2 pairs are needed for an efficient test. Redundancy increases with sibship size. Using simulated data on the null hypothesis of no linkage, we have considered equal and unequal weights. Unequal weights lose power as measured by the equivalent number of observations, and goodness of fit to the theoretical distribution is degraded. The Fisher z(r) test with equally weighted pairs is more reliable than any t(r) test based on conjectured degrees of freedom, but significance levels must be established by simulation if the number of pairs is small or redundancy is large. An approach to parametric analysis through nuisance parameters is discussed.</abstract><cop>Basel, Switzerland</cop><pub>S. Karger</pub><pmid>8537078</pmid><doi>10.1159/000154299</doi><tpages>8</tpages></addata></record> |
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subjects | Alleles Biological and medical sciences Classical genetics, quantitative genetics, hybrids Fundamental and applied biological sciences. Psychology Genetic Linkage Genetics of eukaryotes. Biological and molecular evolution Humans Lod Score Methods, theories and miscellaneous Models, Genetic Original Paper Wills |
title | Nonparametric Tests for Linkage with Dependent Sib Pairs |
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