Variable selection is a difficult problem in statistical model building. Identification of cost efficient diagnostic factors is very important to health researchers, but most variable selection methods do not take into account the cost of collecting data for the predictors. The trade off between...

OBJECTIVE: We sought to determine whether lesbians have higher rates of overweight and obesity than women of other sexual orientations.METHODS: We compared population estimates of overweight and obesity across sexual orientation groups, using data from the 2002 National Survey of Family...

Background: Local Ontario Early Years Centres (OEYCs) collect timely and relevant local data, but knowledge translation is needed for the data to be useful. Maps represent an ideal tool to interpret local data. While geographic information system (GIS) technology is available, it is less clear...

Background: Organizations that collect substantial data for decision-making purposes are often characterized as being 'data rich' but 'information poor'. Maps and mapping tools can be very useful for research transfer in converting locally collected data into information. Challenges involved in...

Background: An important issue in prediction modeling of multivariate data is the measure of dependence structure. The use of Pearson's correlation as a dependence measure has several pitfalls and hence application of regression prediction models based on this correlation may not be an...

Background: In this paper we propose the use of the within-subject coefficient of variation as an index of a measurement's reliability. For continuous variables and based on its maximum likelihood estimation we derive a variance-stabilizing transformation and discuss confidence interval...

In this thesis, we propose to analyze panel count data using a spline-basedsieve generalized estimating equation method with a semiparametric proportional mean model E(N(t)|Z) = Λ0(t) eβT0Z. The natural log of the baseline mean function, logΛ0(t), is approximated by a monotone cubic B-spline...

An important challenge in statistical modeling involves determining an appropriate structural form for a model to be used in making inferences and predictions. Missing data is a very common occurrence in most research settings and can easily complicate the model selection problem. Many useful...

One of the most frequently used regression models for survival data was proposed by Sir David Cox in 1972, the proportional hazards (PH) model. Even though numerous goodness-of-fit tests have been proposed for the PH model, model assumptions are checked infrequently by researchers utilizing it...

A one factor experimental design is developed based on the potential observable outcome framework, sampling from finite population of units and random allocation of treatments. No assumptions are made about the distribution of units and distribution of treatments. We introduce sampling and...