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Using the confidence interval confidently [PDF]
Journal of Thoracic Disease, 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.
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Correcting the Bias Correction for the Bootstrap Confidence Interval in Mediation Analysis. [PDF]
Front 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.
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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
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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
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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
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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
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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
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A second-order efficient empirical Bayes confidence interval [PDF]
, 2014 We introduce a new adjusted residual maximum likelihood method (REML) in the context of producing an empirical Bayes (EB) confidence interval for a normal mean, a problem of great interest in different small area applications.
Lahiri, Partha, Yoshimori, Masayo
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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
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Admissibility of the usual confidence interval in linear regression [PDF]
Admissibility of the usual confidence interval in linear
regression. Electronic Journal of Statistics, 4, 300-312 (2010), 2010 Consider a linear regression model with independent and identically normally distributed random errors. Suppose that the parameter of interest is a specified linear combination of the regression parameters. We prove that the usual confidence interval for
Giri, Khageswor +2 more
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