Glidden and Liang [2002] have raised important issues regarding ascertainment adjustment in the framework of variance-components modeling for complex genetic traits. While the structure of the authors' logistic variance-component model is simple, ascertainment issues arising with this model are like
Remarks on ascertainment
✍ Scribed by W. J. Ewens; Nereda C. E. Shute
- Publisher
- John Wiley and Sons
- Year
- 1989
- Tongue
- English
- Weight
- 326 KB
- Volume
- 6
- Category
- Article
- ISSN
- 0741-0395
No coin nor oath required. For personal study only.
✦ Synopsis
Genetic Analysis Workshop data come from various sources, with possibly different ascertainment procedures in each. It is plausible that classical ascertainment models do not accurately describe the ascertainment process in each data source. For this reason, we review the biases which can arise from an incorrect specification on the ascertainment process and discuss their relevance for the GAWS data analysis.
📜 SIMILAR VOLUMES
The discussions of and add considerable insight to the topic of ascertainment adjustment in genetic variance component models. The authors are in agreement on a broad range of issues, i.e., that the problem of ascertainment bias in the presence of unmeasured heterogeneity is compelling and more co
The complex diseases continue to provide new challenges for genetic epidemiology. In the current edition of Genetic Epidemiology, Glidden and Liang [2002] consider the effect of latent heterogeneity in disease risk on ascertainmentadjusted parameter estimates, particularly in variance components mod
2181 336 2d d-r b ( 2 4 , 4 4 , . . . . , (2d--2)9 N2r = ( -' I (4r+'L) (4r-t-4) , . . . . (4d-2) ( 4 q 2d-1 dr c&:4y, . . . (2d--2)') 'yr-1--( -' I (4r) (4r+B). . . . (4d-4) (4d-2) d-r ctI:62 . . . (2d (4r-t-L) (4r+4) . . . (4d-2) (4d)