Regression models for cohort mortality studies

Regression Models for Air Pollutionand Daily Mortality : Analysis

Interpreting regression models in clinical outcome studies.

Measuring the outcome of an intervention is central to the practice of evidence based medicine, and most research papers evaluating patient outcomes now incorporate some form of patient-based metric, such as questionnaires or performance tests. Once an outcome has been defined, researchers typically want to know if any other factors can influence the result. This is typically assessed with regr...

Derivation of regression models for pan evaporation estimation

Evaporation is an essential component of hydrological cycle. Several meteorologicalfactors play role in the amount of pan evaporation. These factors are often related to eachother. In this study, a multiple linear regression (MLR) in conjunction with PrincipalComponent Analysis (PCA) was used for modeling of pan evaporation. After thestandardization of the variables, independent components were...

Inference for Censored Quantile Regression Models in Longitudinal Studies

We develop inference procedures for longitudinal data where some of the measurements are censored by fixed constants. We consider a semi-parametric quantile regression model that makes no distributional assumptions. Our research is motivated by the lack of proper inference procedures for data from biomedical studies where measurements are censored due to a fixed quantification limit. In such st...

Regression models for twin studies: a critical review.

Twin studies have long been recognized for their value in learning about the aetiology of disease and specifically for their potential for separating genetic effects from environmental effects. The recent upsurge of interest in life-course epidemiology and the study of developmental influences on later health has provided a new impetus to study twins as a source of unique insights. Twins are of...