English
Related papers

Related papers: Karl Pearson's meta-analysis revisited

200 papers

Many methods have been developed to estimate the set of relevant variables in a sparse linear model Y= XB+e where the dimension p of B can be much higher than the length n of Y. Here we propose two new methods based on multiple hypotheses…

Statistics Theory · Mathematics 2012-06-12 Florian Rohart

The two-trials rule in drug regulation requires statistically significant results from two pivotal trials to demonstrate efficacy. However, it is unclear how the effect estimates from both trials should be combined to quantify the drug…

Methodology · Statistics 2025-07-08 Samuel Pawel , Małgorzata Roos , Leonhard Held

The ongoing replication crisis in science has increased interest in the methodology of replication studies. We propose a novel Bayesian analysis approach using power priors: The likelihood of the original study's data is raised to the power…

Methodology · Statistics 2023-09-28 Samuel Pawel , Frederik Aust , Leonhard Held , Eric-Jan Wagenmakers

The American Statistical Association (ASA) statement on statistical significance and P-values \cite{wasserstein2016asa} cautioned statisticians against making scientific decisions solely on the basis of traditional P-values. The statement…

Methodology · Statistics 2024-02-22 Abhisek Chakraborty , Megan H. Murray , Ilya Lipkovich , Yu Du

Karl Pearson played an enormous role in determining the content and organization of statistical research in his day, through his research, his teaching, his establishment of laboratories, and his initiation of a vast publishing program. His…

Methodology · Statistics 2008-09-01 Stephen M. Stigler

Rosenthal's (1979) Fail-Safe-Number (FSN) is probably one of the best known statistics in the context of meta-analysis aimed to estimate the number of unpublished studies in meta-analyses required to bring the meta-analytic mean effect size…

Other Statistics · Statistics 2010-10-13 Moritz Heene

Combining the mutual information criterion with a forward feature selection strategy offers a good trade-off between optimality of the selected feature subset and computation time. However, it requires to set the parameter(s) of the mutual…

Machine Learning · Computer Science 2007-09-26 Damien François , Fabrice Rossi , Vincent Wertz , Michel Verleysen

Motivation:Microarray experiments result in large scale data sets that require extensive mining and refining to extract useful information. We demonstrate the usefulness of (nonmetric) multidimensional scaling (MDS) method in analyzing a…

Genomics · Quantitative Biology 2009-09-29 Y. -h. Taguchi , Y. Oono

We propose a new powerful family of tests of univariate normality. These tests are based on an initial value problem in the space of characteristic functions originating from the fixed point property of the normal distribution in the zero…

Statistics Theory · Mathematics 2020-02-28 Bruno Ebner

This paper presents a model-based method for fusing data from multiple sensors with a hypothesis-test-based component for rejecting potentially faulty or otherwise malign data. Our framework is based on an extension of the classic particle…

Systems and Control · Computer Science 2020-07-31 Matthew A. Wright , Roberto Horowitz

Factor Analysis (FA) is a technique of fundamental importance that is widely used in classical and modern multivariate statistics, psychometrics and econometrics. In this paper, we revisit the classical rank-constrained FA problem, which…

Methodology · Statistics 2017-04-25 Dimitris Bertsimas , Martin S. Copenhaver , Rahul Mazumder

The task of monitoring for a change in the mean of a sequence of Bernoulli random variables has been widely studied. However most existing approaches make at least one of the following assumptions, which may be violated in many real-world…

Computation · Statistics 2015-05-08 Gordon J. Ross , Dimitris K. Tasoulis , Niall M. Adams

Compound Poisson distributions have been employed by many authors to fit experimental data, typically via the method of moments or maximum likelihood estimation. We propose a new technique and apply it to several sets of published data. It…

Methodology · Statistics 2025-04-01 S. R. Mane

We consider a stationary linear AR($p$) model with observations subject to gross errors (outliers). The autoregression parameters as well as the distribution function (d.f.) $G$ of innovations are unknown. The distribution of outliers $\Pi$…

Statistics Theory · Mathematics 2020-04-15 Michael Boldin

Transcriptomic analysis are characterized by being not directly quantitative and only providing relative measurements of expression levels up to an unknown individual scaling factor. This difficulty is enhanced for differential expression…

Methodology · Statistics 2021-03-24 Dorota Desaulle , Céline Hoffmann , Bernard Hainque , Yves Rozenholc

The power prior and its variations have been proven to be a useful class of informative priors in Bayesian inference due to their flexibility in incorporating the historical information by raising the likelihood of the historical data to a…

Methodology · Statistics 2022-04-14 Zifei Han , Keying Ye , Min Wang

Statistical significance of both the original and the replication study is a commonly used criterion to assess replication attempts, also known as the two-trials rule in drug development. However, replication studies are sometimes conducted…

Applications · Statistics 2024-05-31 Leonhard Held , Samuel Pawel , Charlotte Micheloud

In the Bayesian literature on model comparison, Bayes factors play the leading role. In the classical statistical literature, model selection criteria are often devised used cross-validation ideas. Amalgamating the ideas of Bayes factor and…

Statistics Theory · Mathematics 2020-06-12 Debashis Chatterjee , Sourabh Bhattacharya

Any empirical data can be approximated to one of Pearson distributions using the first four moments of the data (Elderton and Johnson, 1969; Pearson, 1895; Solomon and Stephens, 1978). Thus, Pearson distributions made statistical analysis…

Computation · Statistics 2019-12-24 Wei Pan , Xinming An , Qing Yang

Fisher's method prescribes a way to combine p-values from multiple experiments into a single p-value. However, the original method can only determine a combined p-value analytically if all constituent p-values are weighted equally. Here we…

Methodology · Statistics 2020-06-19 Arvind Thiagarajan