Results 11 to 20 of about 3,337,930 (354)
The Automatic Construction of Bootstrap Confidence Intervals
Journal of Computational And Graphical Statistics, 2020 The standard intervals, for example, for nominal 95% two-sided coverage, are familiar and easy to use, but can be of dubious accuracy in regular practice.
B. Efron, B. Narasimhan
semanticscholar +1 more source
Confidence intervals for policy evaluation in adaptive experiments [PDF]
Proceedings of the National Academy of Sciences of the United States of America, 2019 Significance Randomized controlled trials are central to the scientific process, but they can be costly. For example, a clinical trial may assign patients to treatments that are detrimental to them.
semanticscholar +1 more source
Confidence intervals for fMRI activation maps. [PDF]
PLoS ONE, 2013 Neuroimaging activation maps typically color voxels to indicate whether the blood oxygen level-dependent (BOLD) signals measured among two or more experimental conditions differ significantly at that location.
Stephen A Engel, Philip C Burton
doaj +1 more source
Causal inference by using invariant prediction: identification and confidence intervals [PDF]
, 2015 What is the difference between a prediction that is made with a causal model and that with a non‐causal model? Suppose that we intervene on the predictor variables or change the whole environment.
J. Peters +2 more
semanticscholar +1 more source
Genome sequence-based species delimitation with confidence intervals and improved distance functions
BMC Bioinformatics, 2013 For the last 25 years species delimitation in prokaryotes (Archaea and Bacteria) was to a large extent based on DNA-DNA hybridization (DDH), a tedious lab procedure designed in the early 1970s that served its purpose astonishingly well in the absence of ...
Jan P. Meier-Kolthoff +3 more
semanticscholar +1 more source
Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations
European Journal of Epidemiology, 2016 Misinterpretation and abuse of statistical tests, confidence intervals, and statistical power have been decried for decades, yet remain rampant. A key problem is that there are no interpretations of these concepts that are at once simple, intuitive ...
S. Greenland +6 more
semanticscholar +1 more source
Multivariate Confidence Intervals [PDF]
, 2017 Confidence intervals are a popular way to visualize and analyze data distributions. Unlike p-values, they can convey information both about statistical significance as well as effect size. However, very little work exists on applying confidence intervals to multivariate data.
Korpela, Jussi +4 more
openaire +3 more sources
, 1986 This is a review of bootstrap methods, concentrating on basic ideas and applications rather than theoretical considerations. It begins with an exposition of the bootstrap estimate of standard error for one-sample situations.
B. Efron, R. Tibshirani
semanticscholar +1 more source
Generalized Confidence Intervals for Zero-Inflated Pareto Distribution
Mathematics, 2021 This paper considers interval estimations for the mean of Pareto distribution with excess zeros. Three approaches for interval estimation are proposed based on fiducial generalized pivotal quantities (FGPQs), respectively.
Xiao Wang, Xinmin Li
doaj +1 more source
Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs
, 2014 In the regression‐discontinuity (RD) design, units are assigned to treatment based on whether their value of an observed covariate exceeds a known cutoff.
Sebastian Calonico +2 more
semanticscholar +1 more source