Exact Confidence Intervals for Nonconstant Effects by Inverting the Signed Rank Test
نویسنده
چکیده
Wilcoxon’s signed rank test is often inverted, using Walsh averages, to yield exact, distribution free, randomization based confidence intervals for a constant treatment effect or center of symmetry; however, many treatment effects are not constant, so that this interval is not applicable. This article proposes a new way to invert the signed rank test, again using Walsh averages, to produce an exact, distribution free, randomization based confidence interval describing treatment effects that are not constant. The procedure is simple to apply, comparable to the signed rank test itself. Also, the procedure permits a sensitivity analysis in observational studies that estimate treatment effects in the absence of randomization. The method is illustrated using an observational study of the frequency of micronuclei in the cells of alcoholics and matched controls.
منابع مشابه
Exact, Nonparametric Inference When Doses Are Measured With Random Errors
Studies that estimate the effects of exposure to a possibly harmful agent often compare exposed subjects who received varied doses with matched controls who received zero dose. If the doses are measured with error, then one may wish to use the fallible doses to estimate a linear relationship between the unobserved true dose and the observed response. If one is willing to assume that the dose er...
متن کاملDealing with discreteness: making 'exact' confidence intervals for proportions, differences of proportions, and odds ratios more exact.
'Exact' methods for categorical data are exact in terms of using probability distributions that do not depend on unknown parameters. However, they are conservative inferentially. The actual error probabilities for tests and confidence intervals are bounded above by the nominal level. This article examines the conservatism for interval estimation and describes ways of reducing it. We illustrate ...
متن کاملExact maximum coverage probabilities of confidence intervals with increasing bounds for Poisson distribution mean
A Poisson distribution is well used as a standard model for analyzing count data. So the Poisson distribution parameter estimation is widely applied in practice. Providing accurate confidence intervals for the discrete distribution parameters is very difficult. So far, many asymptotic confidence intervals for the mean of Poisson distribution is provided. It is known that the coverag...
متن کاملComment: Randomized Confidence Intervals and the Mid-P Approach
We enjoyed reading the interesting, thought-provoking article by Geyer and Meeden. In our comments we will try to place their work in perspective relative to the original proposals for exact and randomized confidence intervals for the binomial parameter. We propose a fuzzy version of the original binomial randomized confidence interval, due to Stevens (1950). Our approach motivates an existing ...
متن کاملCausal Inference for Binary Data with Interference
Joseph Rigdon: Causal Inference for Binary Data with Interference (Under the direction of Michael Hudgens) Developing methods to quantify the effects of interventions to prevent infectious diseases in the presence of interference is the overall objective of this research. Interference is present when an individual’s outcome is affected by the treatment of any other individuals under study. Firs...
متن کامل