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Using the confidence interval confidently. [PDF]

open access: yesJ Thorac Dis, 2017
Biomedical research is seldom done with entire populations but rather with samples drawn from a population. Although we work with samples, our goal is to describe and draw inferences regarding the underlying population. It is possible to use a sample statistic and estimates of error in the sample to get a fair idea of the population parameter, not as a
Hazra A.
europepmc   +6 more sources

Correcting the Bias Correction for the Bootstrap Confidence Interval in Mediation Analysis. [PDF]

open access: yesFront Psychol, 2022
The bias-corrected bootstrap confidence interval (BCBCI) was once the method of choice for conducting inference on the indirect effect in mediation analysis due to its high power in small samples, but now it is criticized by methodologists for its ...
Tibbe TD, Montoya AK.
europepmc   +2 more sources

Confidence interval for micro-averaged F 1 and macro-averaged F 1 scores. [PDF]

open access: yesAppl Intell (Dordr), 2022
A binary classification problem is common in medical field, and we often use sensitivity, specificity, accuracy, negative and positive predictive values as measures of performance of a binary predictor.
Takahashi K   +3 more
europepmc   +2 more sources

Wind Power Interval Forecasting Based on Confidence Interval Optimization

open access: yesEnergies, 2018
Most of the current wind power interval forecast methods are based on the assumption the point forecast error is subject to a known distribution (such as a normal distribution, beta distribution, etc.).
Xiaodong Yu   +3 more
doaj   +2 more sources

On Confidence Intervals

open access: greenProceedings of the National Academy of Sciences, 1942
Not ...
Edwin B. Wilson
openalex   +5 more sources

Confidence interval estimation for vaccine efficacy against COVID-19 [PDF]

open access: yesFrontiers in Public Health, 2022
This article focuses on the construction of a confidence interval for vaccine efficacy against contagious coronavirus disease-2019 (COVID-19) in a fixed number of events design.
Qinyu Wei, Peng Wang, Ping Yin
doaj   +2 more sources

Confidence interval methods for antimicrobial resistance surveillance data [PDF]

open access: yesAntimicrobial Resistance and Infection Control, 2021
Background Antimicrobial resistance (AMR) is one of the greatest global health challenges today, but burden assessment is hindered by uncertainty of AMR prevalence estimates.
Erta Kalanxhi   +3 more
doaj   +2 more sources

Alternatives to P value: confidence interval and effect size [PDF]

open access: yesKorean Journal of Anesthesiology, 2016
The previous articles of the Statistical Round in the Korean Journal of Anesthesiology posed a strong enquiry on the issue of null hypothesis significance testing (NHST).
Dong Kyu Lee
doaj   +2 more sources

The fallacy of placing confidence in confidence intervals [PDF]

open access: yesPsychonomic Bulletin & Review, 2015
Interval estimates - estimates of parameters that include an allowance for sampling uncertainty - have long been touted as a key component of statistical analyses. There are several kinds of interval estimates, but the most popular are confidence intervals (CIs): intervals that contain the true parameter value in some known proportion of repeated ...
Morey, Richard D   +4 more
openaire   +10 more sources

Sample size estimation for correlations with pre-specified confidence interval [PDF]

open access: yesTutorials in Quantitative Methods for Psychology, 2014
A common measure of association between two variables x and y is the bivariate Pearson correlation coefficient rho(x,y) that characterizes the strength and direction of any linear relationship between x and y.
Murray Moinester, Ruth Gottfried
doaj   +2 more sources

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