### Abstract

The robust sib-pair method introduced by Haseman and Elston (1972) is one of the most widely circulated allele-sharing methods for linkage analysis. The procedure evaluates linkage by significance testing of a regression coefficient and, hence, a standard t-test has traditionally been applied despite known violations of the statistical assumptions underlying the test. We present a permutation based reference distribution for the estimate of the regression coefficient that is motivated by genetic principles rather than by standard regression testing procedures. The permutation test approximates Mendelian co-segregation under the null hypothesis of no linkage, making it a very natural approach. Theory and simulations show that the conventional t-test approximates the permutation test quite well, even when dependent sib pairs are used for analysis. These results thus indirectly address concerns over the t-test. To illustrate the permutation test using real data we applied the procedure to two lipoprotein systems that have been well characterized.

Original language | English (US) |
---|---|

Pages (from-to) | 79-87 |

Number of pages | 9 |

Journal | Annals of Human Genetics |

Volume | 61 |

Issue number | 1 |

State | Published - Jan 1997 |

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### ASJC Scopus subject areas

- Genetics(clinical)
- Genetics

### Cite this

*Annals of Human Genetics*,

*61*(1), 79-87.

**A permutation test for the robust sib-pair linkage method.** / Wan, Y.; Cohen, J.; Guerra, R.

Research output: Contribution to journal › Article

*Annals of Human Genetics*, vol. 61, no. 1, pp. 79-87.

}

TY - JOUR

T1 - A permutation test for the robust sib-pair linkage method

AU - Wan, Y.

AU - Cohen, J.

AU - Guerra, R.

PY - 1997/1

Y1 - 1997/1

N2 - The robust sib-pair method introduced by Haseman and Elston (1972) is one of the most widely circulated allele-sharing methods for linkage analysis. The procedure evaluates linkage by significance testing of a regression coefficient and, hence, a standard t-test has traditionally been applied despite known violations of the statistical assumptions underlying the test. We present a permutation based reference distribution for the estimate of the regression coefficient that is motivated by genetic principles rather than by standard regression testing procedures. The permutation test approximates Mendelian co-segregation under the null hypothesis of no linkage, making it a very natural approach. Theory and simulations show that the conventional t-test approximates the permutation test quite well, even when dependent sib pairs are used for analysis. These results thus indirectly address concerns over the t-test. To illustrate the permutation test using real data we applied the procedure to two lipoprotein systems that have been well characterized.

AB - The robust sib-pair method introduced by Haseman and Elston (1972) is one of the most widely circulated allele-sharing methods for linkage analysis. The procedure evaluates linkage by significance testing of a regression coefficient and, hence, a standard t-test has traditionally been applied despite known violations of the statistical assumptions underlying the test. We present a permutation based reference distribution for the estimate of the regression coefficient that is motivated by genetic principles rather than by standard regression testing procedures. The permutation test approximates Mendelian co-segregation under the null hypothesis of no linkage, making it a very natural approach. Theory and simulations show that the conventional t-test approximates the permutation test quite well, even when dependent sib pairs are used for analysis. These results thus indirectly address concerns over the t-test. To illustrate the permutation test using real data we applied the procedure to two lipoprotein systems that have been well characterized.

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UR - http://www.scopus.com/inward/citedby.url?scp=0031054384&partnerID=8YFLogxK

M3 - Article

VL - 61

SP - 79

EP - 87

JO - Annals of Human Genetics

JF - Annals of Human Genetics

SN - 0003-4800

IS - 1

ER -