Results 151 to 160 of about 363,972 (190)

Confidence, power and distributive preferences

Mind & Society, 2020
The aims of this study were twofold, to: (1) examine the behavior displayed by participants who expected to be nominated for donor roles in dictator games wherein initial endowments of players are determined by lottery and (2) investigate the conduct of donors who were confident in their good fortune in relation to their power as they redistributed the
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Confidence distributions in statistical inference

AIP Conference Proceedings, 2011
This paper reviews the new methodology for statistical inferences. Point estimators, confidence intervals and p—values are fundamental tools for frequentist statisticians. Confidence distributions, which can be viewed as “distribution estimators”, are often convenient for constructing all of the above statistical procedures and more.
Sergey Bityukov, Nikolai Krasnikov, Saralees Nadarajah, Vera Smirnova, Ali Mohammad-Djafari, Jean-François Bercher, Pierre Bessiére   +6 more
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Model-averaged confidence distributions

Environmental and Ecological Statistics, 2019
Model averaging is commonly used to allow for model uncertainty in parameter estimation. As well as providing a point estimate that is a natural compromise between the estimates from different models, it also provides confidence intervals with better coverage properties, compared to those based on a single best model.
David Fletcher, Peter W. Dillingham, Peter W. Dillingham, Jiaxu Zeng   +3 more
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Confidence Distribution for the Ability Parameter of the Rasch Model

Psychometrika, 2021
In this paper, we consider the Rasch model and suggest novel point estimators and confidence intervals for the ability parameter. They are based on a proposed confidence distribution (CD) whose construction has required to overcome some difficulties essentially due to the discrete nature of the model. When the number of items is large, the computations
Piero Veronese, Eugenio Melilli
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Confidence bands for the laplace distribution

Journal of Statistical Computation and Simulation, 1982
Based on a random sample from the Laplace population with unknown shape and scale parameters, one- and two-sided confidence bands on the entire cumulative distribution function and simultaneous confidence intervals for the interval probabilities under the distribution are constructed using Kolmogorov–Smirnov type statistics. Small sample and asymptotic
R. Srinivasan, Robert M. Wharton
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Confidence intervals for the parameters of the logistic distribution

Biometrika, 1970
where a and b are location and scale parameters. The range of application of the logistic distribution as a probability model to describe random phenomenon covers such areas as psychosensory response systems, population growth, bioassay, life tests and physiochemical phenomena.
William L. Harkness, Lawrence A. Klimko, Charles E. Antle   +2 more
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Confidence Regions for Distribution Bounds

IEEE Transactions on Reliability, 1980
This paper considers the problem of constructing an s-confidence region for a pair of parameters which together mark the bounds of a distribution. The problem is solved, and a table provided, for a rectangular distribution; the solution is then generalized.
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Sampling Distributions I: Confidence

1998
You have been studying a strategy for data collection which involves the use of randomization. At first glance, it might seem that this deliberate introduction of uncertainty would only compound the problem of drawing reliable conclusions from the data collected.
Beth Chance, Allan J. Rossman
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On Cox’s Confidence Distribution

1987
A confidence distribution function is a graphical tool for flexible statistical analyses. It provides one- and two-sided tests of simple and interval hypotheses for any size, central and symmetrical confidence intervals of any level. Given an interval of equivalent values, it quantifies the strength of evidence for “no material difference” between two ...
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Improved approximations for confidence distributions

2016
Previous chapters have developed concepts and methodology pertaining to confidence distributions and related inference procedures. Some of these methods take the form of generally applicable recipes, via log-likelihood profiles, deviances and first-order large-sample approximations to the distribution of estimators of the focus estimands in question ...
Tore Schweder, Nils Lid Hjort
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