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Twin concordances test for ascertained trichotomous traits data
Author(s) -
Huang Jason Kunming,
Tai John Jen
Publication year - 2006
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.2573
Subject(s) - concordance , pairwise comparison , statistics , estimator , odds , mathematics , computer science , econometrics , biology , genetics , logistic regression
In human genetics, twin studies are widely underwent for investigation of the genetic influence on diseases. There are several measures that had been proposed to evaluate the similarity between two twins for dichotomous traits when the twins are sampled at random. These measures include the correlations, odds ratios, and casewise and pairwise concordances. When data are sampled through an ascertainment procedure, truncated data are formed. Under this circumstance, odds ratio cannot be defined and correlations cannot be correctly estimated. However, concordance measures for dichotomous traits can still be estimated using the likelihood method. On the other hand, though theoretically concordance measures can be extended to trichotomous traits, how to define them and to derive their estimators for ascertained trichotomous traits data have not been thoroughly discussed. In this study, we aim to address several relevant issues for ascertained trichotomous traits data. We define two new (casewise and pairwise) concordance measures for trichotomous traits and demonstrate how to apply a so‐called ‘self‐contained subsets method (SCSM)’ to estimation of twin concordances for ascertained data. We show that this method can obtain the same estimates as the likelihood method in an easier way and derive the asymptotic variances of the SCSM estimates under ascertainment. We establish the testing procedure for test of the equality of concordance measures between monozygotic twin pairs and dizygotic twin pairs, and illustrate the methods with a real data set and conduct Monte Carlo simulation to investigate its power performance. Copyright © 2006 John Wiley & Sons, Ltd.