Linkage analysis of complex diseases raises a number of important methodological problems. One of them concerns the clinical classification of disease phenotypes. In this study, we investigate the effects of false positive misclassification on the estimation of the recombination fraction and on the
On the asymptotic behavior of the estimate of the recombination fraction under the null hypothesis of no linkage when the model is misspecified
β Scribed by Dr. John A. Williamson; Christopher I. Amos
- Publisher
- John Wiley and Sons
- Year
- 1990
- Tongue
- English
- Weight
- 535 KB
- Volume
- 7
- Category
- Article
- ISSN
- 0741-0395
No coin nor oath required. For personal study only.
β¦ Synopsis
We show that under the null hypothesis of no linkage the maximum likelihood estimator of the recombination fraction converges to 1/2 even when the trait-related parameter values in the likelihood function are misspecified. Furthermore, we show that under the null hypothesis of no linkage, but with misspecified trait-related parameter values, the negative of twice the natural logarithm of the likelihood ratio statistic still has a limiting chi-square distribution with 1 degree of freedom.
π SIMILAR VOLUMES
The asymptotic distribution of one-step Newton-Raphson estimates is established for a regression model with random carriers and heteroscedastic errors under mild conditions. We also include a class of robust estimates deΓΏned as the solution of an implicit equation, such as the MM-estimates.