Before running a calculation code, it is necessary to collect and select the required entry data, data being a fundamental element upon which reasoning as well as research are based. In order to be rigorous, these practical elements should be managed in parallel with the modelling activities, aiming at common targets. For example, such a view is necessary for building relevant experimental desi...

University of Pittsburgh Cancer Institute Paper or Poster Presentation Abstract Teaching students the skills of planning and interpreting experiments is difficult. Students tend to focus on obtaining desired outcomes rather than on understanding causes and effects. Inquiry skills are increasingly important for students entering the health professions who may later conduct large-scale research s...

In previous chapters we analyzed data from so-called one-way experimental designs, in which subjects were randomly assigned to groups that di↵ered on a single treatment or grouping variable. In this chapter we will analyze data from factorial experiments. Factorial experiments contain two or more experimental variables. In a completely crossed factorial experiment, each level of every variable ...

Increasingly, statisticians and reliability engineers in industry are being asked to analyze reliability data. Because of the complicated nature of the data and models that are often encountered in reliability studies, statistical methods and corresponding software needed for appropriate analyses are not developed as well as methods and software needed for the analysis of standard experimental ...

S INCE Kiefer (1959) debuted the idea of optimal design of experiments, a vast literature has grown up around the notion of choosing a design based on some numerical criterion. The most common is D-optimality, which chooses the design minimizing the generalized variance of the regression parameter estimates. Though standard designs can be used in most design situations, optimal procedures are u...

This paper discusses social mechanisms of discrimination and reviews existing field experimental designs for their identification. We first explicate two social mechanisms proposed in the literature, animus-driven and statistical discrimination, to explain differential treatment based on ascriptive characteristics. We then present common approaches to study discrimination based on observational...

We present details about how the functions provided in pauwels2014 can be used to reproduce the results presented in [1]. We also describe how the system, model specifications and experimental settings were represented. The goal is to provide one with the capacity to reproduce research results to potentially adapt the method to other settings.

One of the central challenges to studying highly skilled performance in the laboratory is methodological. It is necessary to develop standardized methods that allow investigators to make experts repeatedly reproduce their superior performance in the laboratory. The recent increase in demand for translational research has raised related issues of how everyday phenomena, such as successful clinic...

Many authors make distinctions between clinical trial designs derived using “group sequential designs” (e.g., O’Brien-Fleming or Pocock designs), “error spending functions” (e.g., Lan & DeMets or Hwang, Shih, & DeCani), “stochastic curtailment” (e.g., conditional power or Bayesian predictive power), and “Bayesian designs” based on posterior probabilities. However, in RCTdesign we regard these a...