Computations for the familial analysis of binary traits

Subscribe to email list

Please select the email list(s) to which you wish to subscribe.

You are here

Computations for the familial analysis of binary traits

TitleComputations for the familial analysis of binary traits
Publication TypeJournal Article
Year of Publication2005
AuthorsJoe, H, Latif, AHMM
JournalComputational Statistics
Volume20
Pagination439-448
ISSN0943-4062
Abstract

For familial aggregation of a binary trait, one method that has been used is the GEE2 (generalized estimating equation) method corresponding to a multivariate logit model. We solve the complex estimating equations for the GEE2 method using an automatic differentiation software which computes the derivatives of a function numerically using the chain rule of the calculus repeatedly on the elementary operations of the function. Based on this, we are able to show in a simulation study that the GEE2 estimates are quite close to the maximum likelihood estimates assuming a multivariate logit model, and that the GEE2 method is computationally faster when the dimension or family size is larger than four.

DOI10.1007/BF02741307