@article { ISI:000232133200005,
	title = {Computations for the familial analysis of binary traits},
	journal = {Computational Statistics},
	volume = {20},
	number = {3},
	year = {2005},
	pages = {439-448},
	abstract = {<p>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.</p>
},
	issn = {0943-4062},
	doi = {10.1007/BF02741307},
	author = {Joe, H and Latif, A H M M}
}
