Further properties of frequentist confidence intervals in regression that utilize uncertain prior information [PDF]
Further properties of frequentist confidence intervals in
regression that utilize uncertain prior information. Australian & New Zealand
Journal of Statistics, 55, 259-270 (2013), 2011 Consider a linear regression model with n-dimensional response vector, regression parameter \beta = (\beta_1, ..., \beta_p) and independent and identically N(0, \sigma^2) distributed errors. Suppose that the parameter of interest is \theta = a^T \beta where a is a specified vector.
arxiv
Confidence with confidence intervals [PDF]
British Journal of Anaesthesia, 2005 M.O. Columb, H.E. Thomson
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Confidence Trick: The Interpretation of Confidence Intervals [PDF]
Canadian Journal of Science, Mathematics and Technology Education, 2014 The frequent misinterpretation of the nature of confidence intervals by students has been well documented. This article examines the problem as an aspect of the learning of mathematical definitions and considers the tension between parroting mathematically rigorous, but essentially uninternalized, statements on the one hand and expressing imperfect but
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Confidence interval or p-value?: part 4 of a series on evaluation of scientific publications.
Deutsches Ärzteblatt International, 2009 BACKGROUND An understanding of p-values and confidence intervals is necessary for the evaluation of scientific articles. This article will inform the reader of the meaning and interpretation of these two statistical concepts.
J. du Prel +3 more
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Rank conditional coverage and confidence intervals in high dimensional problems [PDF]
arXiv, 2017 Confidence interval procedures used in low dimensional settings are often inappropriate for high dimensional applications. When a large number of parameters are estimated, marginal confidence intervals associated with the most significant estimates have very low coverage rates: They are too small and centered at biased estimates. The problem of forming
arxiv
Variable-width confidence intervals in Gaussian regression and penalized maximum likelihood estimators [PDF]
arXiv, 2010 Hard thresholding, LASSO , adaptive LASSO and SCAD point estimators have been suggested for use in the linear regression context when most of the components of the regression parameter vector are believed to be zero, a sparsity type of assumption. Potscher and Schneider, 2010, Electronic Journal of Statistics, have considered the properties of fixed ...
arxiv
Simple Confidence Intervals for MCMC Without CLTs [PDF]
arXiv, 2018 This short note argues that 95% confidence intervals for MCMC estimates can be obtained even without establishing a CLT, by multiplying their widths by 2.3.
arxiv
A Note on Confidence Interval Estimation and Margin of Error
, 2010 Confidence interval estimation is a fundamental technique in statistical inference. Margin of error is used to delimit the error in estimation. Dispelling misinterpretations that teachers and students give to these terms is important.
D. Gilliland, Vincent F. Melfi
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Simultaneous Confidence Interval Estimation [PDF]
, 1953 Sasanka Roy, R. C. Bose
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General concepts in biostatistics and clinical epidemiology: Random error and systematic error
Medwave, 2019 Resumen La investigación biomédica, particularmente la que involucra a seres humanos, está siempre sometida a fuentes de error que deben ser reconocidas.
Felipe Barraza +3 more
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