Add to ORKGThe motivation for randomization inference and sensitivity analysis is reviewed. New methods are discussed for inverting randomization tests to provide interval estimates of the magnitude of treatment e¤ects
A sensitivity analysis in an observational study determines the magni-tude of bias from nonrandom tr...
In estimating the effect of an ordered treatment τ on a count response y with an observational data ...
Many issues of interest to social scientists and policy makers are of a sensitive nature in the sens...
This chapter provides a framework for conceptualizing randomization in clinical trials and for linki...
This thesis unites three papers discussing different approaches for estimating treatment effects, ei...
Summary. Huber’s m-estimates use an estimating equation in which observations are permitted a con-tr...
This thesis unites three papers discussing different approaches for estimating treatment effects, ei...
The aim of this paper is to provide a new design strategy for response adaptive randomization in th...
Statistical models are simplification of reality; we rarely expect the model to be exactly true. Ne...
This dissertation explores methodological topics in the analysis of randomized experiments, with a f...
We demonstrate that clinical trials using response adaptive randomized treatment assignment rules ar...
A sensitivity analysis displays the increase in uncertainty that attends an inference when a key ass...
Randomization tests for alternating treatments designs, multiple baseline designs, and withdrawal/re...
Randomization tests have been suggested as a method for analyzing the data from single-case designs....
Response and remission rates at each assessment point after randomization by treatment condition.</p
A sensitivity analysis in an observational study determines the magni-tude of bias from nonrandom tr...
In estimating the effect of an ordered treatment τ on a count response y with an observational data ...
Many issues of interest to social scientists and policy makers are of a sensitive nature in the sens...
This chapter provides a framework for conceptualizing randomization in clinical trials and for linki...
This thesis unites three papers discussing different approaches for estimating treatment effects, ei...
Summary. Huber’s m-estimates use an estimating equation in which observations are permitted a con-tr...
This thesis unites three papers discussing different approaches for estimating treatment effects, ei...
The aim of this paper is to provide a new design strategy for response adaptive randomization in th...
Statistical models are simplification of reality; we rarely expect the model to be exactly true. Ne...
This dissertation explores methodological topics in the analysis of randomized experiments, with a f...
We demonstrate that clinical trials using response adaptive randomized treatment assignment rules ar...
A sensitivity analysis displays the increase in uncertainty that attends an inference when a key ass...
Randomization tests for alternating treatments designs, multiple baseline designs, and withdrawal/re...
Randomization tests have been suggested as a method for analyzing the data from single-case designs....
Response and remission rates at each assessment point after randomization by treatment condition.</p
A sensitivity analysis in an observational study determines the magni-tude of bias from nonrandom tr...
In estimating the effect of an ordered treatment τ on a count response y with an observational data ...
Many issues of interest to social scientists and policy makers are of a sensitive nature in the sens...