Results 31 to 40 of about 1,356,793 (315)

Automatic Features Extraction Integrated With Exact Gaussian Process for Respiratory Rate and Uncertainty Estimations

open access: yesIEEE Access, 2023
Respiratory rate monitoring has become necessary for people with respiratory diseases, especially those living alone. Sudden changes in respiratory rate (RR) in these individuals may indicate a severe illness.
Soojeong Lee, Gangseong Lee
doaj   +1 more source

Wild Bootstrap for Fuzzy Regression Discontinuity Designs: Obtaining Robust Bias-Corrected Confidence Intervals

open access: yesEconometrics Journal, 2020
This paper develops a novel wild bootstrap procedure to construct robust bias-corrected valid confidence intervals for fuzzy regression discontinuity designs, providing an intuitive complement to existing robust bias-corrected methods.
Yang He, Otávio Bartalotti
semanticscholar   +1 more source

Evaluation of jackknife and bootstrap for defining confidence intervals for pairwise agreement measures.

open access: yesPLoS ONE, 2011
Several research fields frequently deal with the analysis of diverse classification results of the same entities. This should imply an objective detection of overlaps and divergences between the formed clusters. The congruence between classifications can
Ana Severiano   +4 more
doaj   +1 more source

Do metabolic factors increase the risk of thyroid cancer? a Mendelian randomization study

open access: yesFrontiers in Endocrinology, 2023
BackgroundEpidemiological studies emphasize the link between metabolic factors and thyroid cancer. Using Mendelian randomization (MR), we assessed the possible causal impact of metabolic factors on thyroid cancer for the first time.MethodsSummary ...
Weiwei Liang, FangFang Sun
doaj   +1 more source

Robust Confidence Intervals for Average Treatment Effects Under Limited Overlap

open access: yesSocial Science Research Network, 2017
Estimators of average treatment effects under unconfounded treatment assignment are known to become rather imprecise if there is limited overlap in the covariate distributions between the treatment groups.
C. Rothe
semanticscholar   +1 more source

Confidence Intervals For An Effect Size When Variances Are Not Equal [PDF]

open access: yes, 2006
Confidence intervals must be robust in having nominal and actual probability coverage in close agreement. This article examined two ways of computing an effect size in a two-group problem: (a) the classic approach which divides the mean difference by a ...
Algina, James   +2 more
core   +2 more sources

Use of the bootstrap in analysing cost data from cluster randomised trials: some simulation results

open access: yesBMC Health Services Research, 2004
Background This work has investigated under what conditions confidence intervals around the differences in mean costs from a cluster RCT are suitable for estimation using a commonly used cluster-adjusted bootstrap in preference to methods that utilise ...
Flynn Terry N, Peters Tim J
doaj   +1 more source

Confidence interval based parameter estimation--a new SOCR applet and activity. [PDF]

open access: yesPLoS ONE, 2011
Many scientific investigations depend on obtaining data-driven, accurate, robust and computationally-tractable parameter estimates. In the face of unavoidable intrinsic variability, there are different algorithmic approaches, prior assumptions and ...
Nicolas Christou, Ivo D Dinov
doaj   +1 more source

A simple remedy for overprecision in judgment [PDF]

open access: yesJudgment and Decision Making, 2010
Overprecision is the most robust type of overconfidence. We present a new method that significantly reduces this bias and offers insight into its underlying cause.
Uriel Haran   +2 more
doaj   +3 more sources

Which Robust Regression Technique Is Appropriate Under Violated Assumptions? A Simulation Study

open access: yesMethodology, 2023
Ordinary least squares (OLS) regression is widely employed for statistical prediction and theoretical explanation in psychology studies. However, OLS regression has a critical drawback: it becomes less accurate in the presence of outliers and non-random ...
Jaejin Kim, Johnson Ching-Hong Li
doaj   +1 more source

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