Using the confidence interval confidently. [PDF]
J 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
Confidence interval for micro-averaged F 1 and macro-averaged F 1 scores. [PDF]
Appl 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
Energies, 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
Confidence interval estimation for vaccine efficacy against COVID-19 [PDF]
Frontiers 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]
Antimicrobial 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]
Korean 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]
Psychonomic 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 +9 more sources
Sample size estimation for correlations with pre-specified confidence interval [PDF]
Tutorials 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
An Elaboration on Sample Size Planning for Performing a One-Sample Sensitivity and Specificity Analysis by Basing on Calculations on a Specified 95% Confidence Interval Width [PDF]
Diagnostics, 2023 Sample size calculation based on a specified width of 95% confidence interval will offer researchers the freedom to set the level of accuracy of the statistics that they aim to achieve for a particular study.
Mohamad Adam Bujang
doaj +2 more sources
Confidence Interval Estimation of Interaction
Epidemiology, 1992 Relative excess risk due to interaction, the proportion of disease among those with both exposures that is attributable to their interaction, and the synergy index have been proposed as measures of interaction in epidemiologic studies.
David W. Hosmer, Stanley Lemeshow
openalex +2 more sources