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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1967 3
1972 1
1974 2
1975 2
1976 3
1977 3
1978 4
1979 3
1980 8
1981 4
1982 15
1983 11
1984 12
1985 24
1986 26
1987 29
1988 31
1989 52
1990 43
1991 46
1992 48
1993 39
1994 57
1995 59
1996 77
1997 85
1998 87
1999 110
2000 138
2001 165
2002 184
2003 270
2004 334
2005 433
2006 498
2007 566
2008 607
2009 715
2010 878
2011 960
2012 1092
2013 1098
2014 1058
2015 1159
2016 1205
2017 1258
2018 1247
2019 1279
2020 1564
2021 1858
2022 2112
2023 1828
2024 608

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20,702 results

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Page 1
A review of instrumental variable estimators for Mendelian randomization.
Burgess S, Small DS, Thompson SG. Burgess S, et al. Stat Methods Med Res. 2017 Oct;26(5):2333-2355. doi: 10.1177/0962280215597579. Epub 2015 Aug 17. Stat Methods Med Res. 2017. PMID: 26282889 Free PMC article. Review.
Under the assumption that a single instrumental variable or a set of instrumental variables for the exposure is available, the causal effect of the exposure on the outcome can be estimated. There are several methods available for instrumental variable estimation; we …
Under the assumption that a single instrumental variable or a set of instrumental variables for the exposure is available, the causal effect …
Empirical Bayes methods for stabilizing incidence rates before mapping.
Devine OJ, Louis TA, Halloran ME. Devine OJ, et al. Epidemiology. 1994 Nov;5(6):622-30. doi: 10.1097/00001648-199411000-00010. Epidemiology. 1994. PMID: 7841244 Review.
In this paper, we describe the empirical Bayes approach for obtaining stabilized incidence estimates. We begin by deriving Bayes rate estimators and then illustrate how using the observed rates to estimate unknown distributional information lead …
In this paper, we describe the empirical Bayes approach for obtaining stabilized incidence estimates. We begin by deriving …
Empirical Bayes Derivative Estimates.
Deboeck PR. Deboeck PR. Multivariate Behav Res. 2020 May-Jun;55(3):382-404. doi: 10.1080/00273171.2019.1642729. Epub 2019 Aug 7. Multivariate Behav Res. 2020. PMID: 31390884
Given the overlap in the specification of latent differential equation models and latent growth curve models, and the equivalence of latent growth curve models and mixed models under some conditions, derivatives could be estimated from estimates of random effects. T …
Given the overlap in the specification of latent differential equation models and latent growth curve models, and the equivalence of latent …
An Empirical Bayes Approach to Shrinkage Estimation on the Manifold of Symmetric Positive-Definite Matrices.
Yang CH, Doss H, Vemuri BC. Yang CH, et al. J Am Stat Assoc. 2024;119(545):259-272. doi: 10.1080/01621459.2022.2110877. Epub 2022 Sep 27. J Am Stat Assoc. 2024. PMID: 38590837 Free PMC article.
The James-Stein estimator is an estimator of the multivariate normal mean and dominates the maximum likelihood estimator (MLE) under squared error loss. The original work inspired great interest in developing shrinkage estimators for a variety of probl …
The James-Stein estimator is an estimator of the multivariate normal mean and dominates the maximum likelihood estimator …
Bayesian color constancy.
Brainard DH, Freeman WT. Brainard DH, et al. J Opt Soc Am A Opt Image Sci Vis. 1997 Jul;14(7):1393-411. doi: 10.1364/josaa.14.001393. J Opt Soc Am A Opt Image Sci Vis. 1997. PMID: 9203394 Review.
Second, we construct prior distributions that describe the probability that particular illuminants and surfaces exist in the world. Given a set of photosensor responses, we can then use Bayes's rule to compute the posterior distribution for the illuminants and the s …
Second, we construct prior distributions that describe the probability that particular illuminants and surfaces exist in the world. Given a …
The Bayes Estimators of the Variance and Scale Parameters of the Normal Model With a Known Mean for the Conjugate and Noninformative Priors Under Stein's Loss.
Zhang YY, Rong TZ, Li MM. Zhang YY, et al. Front Big Data. 2022 Jan 3;4:763925. doi: 10.3389/fdata.2021.763925. eCollection 2021. Front Big Data. 2022. PMID: 35047768 Free PMC article.
For the normal model with a known mean, the Bayes estimation of the variance parameter under the conjugate prior is studied in Lehmann and Casella (1998) and Mao and Tang (2012). However, they only calculate the Bayes estimator with respect to a conjug …
For the normal model with a known mean, the Bayes estimation of the variance parameter under the conjugate prior is studied in …
Bayes shrinkage estimator for consistency assessment of treatment effects in multi-regional clinical trials.
Adall SW, Xu J. Adall SW, et al. Pharm Stat. 2021 Nov;20(6):1074-1087. doi: 10.1002/pst.2126. Epub 2021 May 3. Pharm Stat. 2021. PMID: 33942469
We focus on the problem of evaluating applicability of a drug to a specific region of interest under the criterion of preserving a certain proportion of the overall treatment effect in the region. We propose a variant of James-Stein shrinkage estimator in the empirical …
We focus on the problem of evaluating applicability of a drug to a specific region of interest under the criterion of preserving a certain p …
An empirical Bayes approach to improving population-specific genetic association estimation by leveraging cross-population data.
Hsu L, Kooperberg A, Reiner AP, Kooperberg C. Hsu L, et al. Genet Epidemiol. 2023 Feb;47(1):45-60. doi: 10.1002/gepi.22501. Epub 2022 Sep 18. Genet Epidemiol. 2023. PMID: 36116031 Free PMC article.
Extensive simulation studies show that the proposed EB estimators are largely unbiased and improve efficiency compared to the population-specific estimator. ...We apply the proposed EB estimators to a large-scale trans-ancestry GWAS of stroke and demonstrate …
Extensive simulation studies show that the proposed EB estimators are largely unbiased and improve efficiency compared to the populat …
Information-Theoretic Models for Physical Observables.
Bernal-Casas D, Oller JM. Bernal-Casas D, et al. Entropy (Basel). 2023 Oct 14;25(10):1448. doi: 10.3390/e25101448. Entropy (Basel). 2023. PMID: 37895569 Free PMC article.
Following this approach, we study the stationary states with the time-independent Schrodinger's equation to discover that the information could be represented and distributed over a set of quantum harmonic oscillators, one for each independent source of data, whose coordinate for …
Following this approach, we study the stationary states with the time-independent Schrodinger's equation to discover that the information co …
Frequentist Standard Errors of Bayes Estimators.
Lee D, Carroll RJ, Sinha S. Lee D, et al. Comput Stat. 2017 Sep;32(3):867-888. doi: 10.1007/s00180-017-0710-x. Epub 2017 Jan 30. Comput Stat. 2017. PMID: 28943721 Free PMC article.
Frequentist standard errors are a measure of uncertainty of an estimator, and the basis for statistical inferences. Frequestist standard errors can also be derived for Bayes estimators. However, except in special cases, the computation of the standard error o …
Frequentist standard errors are a measure of uncertainty of an estimator, and the basis for statistical inferences. Frequestist stand …
20,702 results
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