Bayesian inferential methods for the two parameter Weibull (and
extreme-value distribution) are presented in a life-testing context. A
practical method of calculating posterior distributions of the two parameters
and a large class of functions of the parameters is presented.
The emphasis is for the situation where the sample information is...
A quantal response model, more general than the usual logistic
model, is introduced. This model takes into account sources of
variability, or experimental error, other than that arising from variability
in response between individual organisms (or other objects on
test). It is assumed that this extra source of variation is...
A distribution-free analysis is proposed for inference concerning
treatment effects in factorial survival experiments in which the recorded
data are grouped by time intervals. A grouped data model is built by
applying the continuous-time Cox regression and life model. This models
the treatments to have multiplicative effects, possibly time dependent,...
Randomized block designs are often modeled by fixed treatment
effects, an additive random effect that is shared by all
observations in the same block, and a second random effect
accounting for the residual variation. With enumerative data, the
residual variation may be related to the treatment and block effects
in...
In regression analysis, random errors in an explanatory variable cause the
usual estimates of its regression coefficient to be biased. Although this problem has
been studied for many years, routine methods have not emerged. This thesis
investigates some aspects of this problem in the setting of analysis of epidemiological
data....
This thesis considers likelihood inferences for generalized linear models with additional
random effects. The likelihood function involved ordinarily cannot be evaluated
in closed form and numerical integration is needed. The theme of the thesis is
a closed-form approximation based on Laplace's method. We first consider a special
yet important case...