Estimation and optimal designing under latent variable models for paired comparisons studies via a multiplicative algorithm

We consider:<BR/> 1. The problem of estimating the parameters of latent variable models such as the Bradley Terry or Thurstone Model by the method of maximum likelihood, given data from a paired comparisons experiment. The parameters of these models can be taken to be weights which are positive and sum to one;<BR/> 2. The problem of determining approximate locally optimal designs for good estimation of these parameters; i.e of determining optimal design weights which are also positive and sum to one

Properties of estimators of baseline hazard functions in a semiparametric cure model

Cox model, Logistic model, Nonparametric baseline hazard, Volterra integral equation, Fredholm integral equation, Asymptotic property,

On composite marginal likelihoods

Clustered data, Computational efficiency, Composite likelihood, Genetics, Longitudinal data, Missing data, Pairwise likelihood, Pseudolikelihood, Spatial data, Statistical efficiency, Survival analysis, Time series,