Literature DB >> 475336

Choice of ascertainment model II. Discrimination between multi-proband models by means of birth order data.

J Stene.   

Abstract

Probability models have been developed for family data, where each family has been selected or ascertained through a group of m probands, where m is a known parameter, not a random variable. The birth orders of the probands among the affected children are reported for each family. It is demonstrated that this information is sufficient for choice of ascertainment model. The conditional probability that an ascertained family with s children has r affected ones, depends, in addition to the segregation parameter, on the birth order of the youngest proband only. By means of the joint distribution of the birth orders of the other probands, it can be demonstrated if the ascertainment takes place through affected children near to or distant from each other in relative birth orders. Statistical methods have been developed for cases with two and cases with m probands.

Entities:  

Mesh:

Year:  1979        PMID: 475336     DOI: 10.1111/j.1469-1809.1979.tb00682.x

Source DB:  PubMed          Journal:  Ann Hum Genet        ISSN: 0003-4800            Impact factor:   1.670


  4 in total

1.  Likelihood formulation of parent-of-origin effects on segregation analysis, including ascertainment.

Authors:  Fatemeh Haghighi; Susan E Hodge
Journal:  Am J Hum Genet       Date:  2001-11-30       Impact factor: 11.025

2.  The essence of single ascertainment.

Authors:  S E Hodge; V J Vieland
Journal:  Genetics       Date:  1996-11       Impact factor: 4.562

3.  Maximum likelihood estimation of genetic parameters of HLA-linked diseases using data from families of various sizes.

Authors:  W J Ewens; C P Clarke
Journal:  Am J Hum Genet       Date:  1984-07       Impact factor: 11.025

4.  Statistical properties of maximum likelihood estimators for genetic parameters of HLA-linked diseases.

Authors:  W J Ewens; R S Spielman
Journal:  Am J Hum Genet       Date:  1985-11       Impact factor: 11.025

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.