In human genetic analysis, data are collected through the so-called 'ascert
ainment procedure'. Statistically this sampling scheme can be thought of as
a multistage sampling method. At the first stage, one or several probands
are ascertained. At the subsequent stages, a sequential sampling scheme is
applied. Sampling in such a way is virtually a nonrandom procedure, which,
in most cases, causes biased estimation which may be intractable, This pape
r focuses on the underlying causes of the intractability problem of ascerta
ined genetic data. Three types of parameters, i.e. target, design and nuisa
nce parameters, are defined as the essences to formulate the true likelihoo
d of a set of data. These parameters are also classified into explicit or i
mplicit parameters depending on whether they can be expressed explicity in
the likelihood function. For ascertained genetic data, a sequential scheme
is regarded as an implicit design parameter, and a true pedigree structure
as an implicit nuisance parameter. The intractability problem is attributed
to loss of information of any implicit parameter in likelihood formulation
. Several approaches to build a likelihood for estimation of the segregatio
n ratio when only an observed pedigree structure is available are proposed.
Copyright (C) 2001 S. Karger AG, Basel.