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作者：Gabriel, Erin E.; Sachs, Michael C.; Jensen, Andreas Kryger
作者单位：University of Copenhagen
摘要：The probability of benefit can be a valuable and meaningful measure of treatment effect. Particularly for an ordinal outcome, it can have an intuitive interpretation. Unfortunately, this measure, and variations of it, are not identifiable even in randomized trials with perfect compliance. There is, for this reason, a long literature on nonparametric bounds for unidentifiable measures of benefit. These have primarily focused on perfect randomized trial settings and one or two specific estimands...
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作者：Dilernia, A. S.; Fiecas, M.; Zhang, L.
作者单位：Grand Valley State University; University of Minnesota System; University of Minnesota Twin Cities
摘要：We derive an asymptotic joint distribution and novel covariance estimator for the partial correlations of a multivariate Gaussian time series given mild regularity conditions. Using our derived asymptotic distribution, we develop a Wald confidence interval and testing procedure for inference of individual partial correlations for time series data. Through simulation we demonstrate that our proposed confidence interval attains higher coverage rates, and our testing procedure attains false posit...
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作者：Thompson, Ryan; Forbes, Catherine S.; Maceachern, Steven N.; Peruggia, Mario
作者单位：Monash University; University System of Ohio; Ohio State University
摘要：Statisticl hypotheses are translations of scientific hypotheses into statements about one or more distributions, often concerning their centre. Tests that assess statistical hypotheses of centre implicitly assume a specific centre, e.g., the mean or median. Yet, scientific hypotheses do not always specify a particular centre. This ambiguity leaves the possibility for a gap between scientific theory and statistical practice that can lead to rejection of a true null. In the face of replicability...
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作者：Rytgaard, H. C. W.; van der Laan, M. J.
作者单位：University of Copenhagen; University of California System; University of California Berkeley
摘要：This paper considers the one-step targeted maximum likelihood estimation methodology for multi-dimensional causal parameters in general survival and competing risk settings where event times take place on the positive real line and are subject to right censoring. We focus on effects of baseline treatment decisions possibly confounded by pretreatment covariates, but remark that our work generalizes to settings with time-varying treatment regimes and time-dependent confounding. We point out two ...
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作者：Cui, Y.; Tchetgen, E. J. Tchetgen
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作者：Wiens, D. P.
作者单位：University of Alberta
摘要：We present a result according to which certain functions of covariance matrices are maximized at scalar multiples of the identity matrix. This is used to show that experimental designs that are optimal under an assumption of independent, homoscedastic responses can be minimax robust, in broad classes of alternate covariance structures. In particular, it can justify the common practice of disregarding possible dependence, or heteroscedasticity, at the design stage of an experiment.
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作者：Hanley, J. A.
作者单位：McGill University
摘要：Statisticians and epidemiologists generally cite the publications of and as the first description and use of conditional logistic regression, while economists cite the book chapter by Nobel laureate McFadden (). We describe the until-now-unrecognized use of, and way of fitting, this model in 1934 by Lionel Penrose and Ronald Fisher.
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作者：Koning, Nick W.
作者单位：Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC
摘要：It is conventionally believed that permutation-based testing methods should ideally use all permutations. We challenge this by showing that we can sometimes obtain dramatically more power by using a tiny subgroup. As the subgroup is tiny, this also comes at a much lower computational cost. Moreover, the method remains valid for the same hypotheses. We exploit this to improve the popular permutation-based Westfall and Young MaxT multiple testing method. We analyse the relative efficiency in a G...
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作者：Henzi, Alexander; Law, Michael
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich
摘要：We consider the problem of independence testing for two univariate random variables in a sequential setting. By leveraging recent developments on safe, anytime-valid inference, we propose a test with time-uniform Type-I error control and derive explicit bounds on the finite-sample performance of the test. We demonstrate the empirical performance of the procedure in comparison to existing sequential and nonsequential independence tests. Furthermore, since the proposed test is distribution-free ...
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作者：Maestrini, Luca; Bhaskaran, Aishwarya; Wand, Matt P.
作者单位：Australian National University; University of Technology Sydney
摘要：A recent article by on generalized linear mixed model asymptotics derived the rates of convergence for the asymptotic variances of maximum likelihood estimators. If m denotes the number of groups and n is the average within-group sample size then the asymptotic variances have orders m-1 and (mn)-1, depending on the parameter. We extend this theory to provide explicit forms of the (mn)-1 second terms of the asymptotically harder-to-estimate parameters. Improved accuracy of statistical inference...
