We consider the problem of point and interval estimation for the risk ratio using double sampling with two-sample misclassified binary data. For such data, it is well-known that the actual data model is unidentifiable. To ...
We present interval estimation methods for comparing Poisson rate parameters from two independent populations with under-reported data for the rate difference and the rate ratio. In addition, we apply the Bayesian paradigm ...
In the clinical setting, the performance of a diagnostic or screening test is often
summarized using the test's true positive rate (TPR) and false positive rate (FPR).
However, estimation of the TPR and FPR for a diagnostic ...
We apply maximum likelihood methods for statistical inference on parameters of interest for three different types of statistical models. The models are a seemingly unrelated regression model, a bivariate Poisson regression ...
Advances in microarray technology have equipped researchers to measure gene expression levels simultaneously from thousands of genes, yielding increasingly large and complex data sets. However, due to the cost and time ...
This dissertation consists of three selected topics in statistical discriminant analysis: dimension reduction, regularization methods, and imputation methods. In Chapter 2 we first derive a new linear dimension-reduction ...
The double-sampling paradigm, which has become an important part of the epidemiological designs, includes two stages. First, individuals are classified into groups by disease and exposure levels using a fallible test, and ...