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Confidence interval based parameter estimation--a new SOCR applet and activity. [PDF]
PLoS 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
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Use of the bootstrap in analysing cost data from cluster randomised trials: some simulation results
BMC 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
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Robust Confidence Intervals for Effect Size in the Two-Group Case [PDF]
, 2005 The probability coverage of intervals involving robust estimates of effect size based on seven procedures was compared for asymmetrically trimming data in an independent two-groups design, and a method that symmetrically trims the data.
Algina, James +2 more
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Globally Robust Confidence Intervals for Location
Dhaka University Journal of Science, 2012 Classical inference considers sampling variability to be the only source of uncertainty, and does not address the issue of bias caused by contamination. Naive robust intervals replace the classical estimates by their robust counterparts without considering the possible bias of the robust point estimates. Consequently, the asymptotic coverage proportion
Jafar A Khan, M. Ershadul Haque
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Confidence Intervals For An Effect Size When Variances Are Not Equal [PDF]
, 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
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Which Robust Regression Technique Is Appropriate Under Violated Assumptions? A Simulation Study
Methodology, 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
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Mathematics, 2020 When the additional sample for the second stage may not be available, one-stage multiple comparisons for exponential median lifetimes with the control under heteroscedasticity including one-sided and two-sided confidence intervals are proposed in this ...
Shu-Fei Wu
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Can the buck always be passed to the highest level of clustering?
BMC Medical Research Methodology, 2016 Background Clustering commonly affects the uncertainty of parameter estimates in epidemiological studies. Cluster-robust variance estimates (CRVE) are used to construct confidence intervals that account for single-level clustering, and are easily ...
Christian Bottomley +3 more
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Robust nonparametric inference for the median
, 2005 We consider the problem of constructing robust nonparametric confidence intervals and tests of hypothesis for the median when the data distribution is unknown and the data may contain a small fraction of contamination.
Yohai, Victor J., Zamar, Ruben H.
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Optimal Bandwidth Choice for Robust Bias Corrected Inference in Regression Discontinuity Designs
, 2020 Modern empirical work in Regression Discontinuity (RD) designs often employs local polynomial estimation and inference with a mean square error (MSE) optimal bandwidth choice.
Calonico, Sebastian +2 more
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