The aim of statistical analysis and inference is to draw meaningful conclusions. In the case where there is prior knowledge of stochastic orderings or inequalities, it is desirable to incorporate this information in the estimation. This avoids possible unrealistic estimates, and may also lead to...

This dissertation compares the parameter estimates obtained from two item response theory (IRT) models: the 1-PL IRT model and the MC1-PL IRT model. Several scenarios were explored in which both unidimensional and multidimensional item-level and personal-level data were used to generate the item...

Considers the analysis of longitudinal data by means of the autogressive or simplex model. The finding by D. Rogosa and J. B. Willett that the quasi-Markov simplex model fits a linear growth curve covariance structure is investigated. Under various circumstances the quasi-Markov simplex model is...

In this dissertation, the generalized score tests based on weighted estimating equationsare proposed for missing covariate data. Their properties, including the effectsof nuisance functions on the forms of the test statistics and efficiency of the tests,are investigated. Different versions of...

Maximum-likelihood estimates of the parameters of stochastic differential equations are consistent and asymptotically efficient, but unfortunately difficult to obtain if a closed-form expression for the transitional probability density function of the process is not available. As a result, a...