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Related papers: A likelihoodist trial procedure

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We outline how modern likelihood theory, which provides essentially exact inferences in a variety of parametric statistical problems, may routinely be applied in practice. Although the likelihood procedures are based on analytical…

Methodology · Statistics 2009-06-23 Alessandra R. Brazzale , Anthony C. Davison

The most popular multiple testing procedures are stepwise procedures based on $P$-values for individual test statistics. Included among these are the false discovery rate (FDR) controlling procedures of Benjamini--Hochberg [J. Roy. Statist.…

Statistics Theory · Mathematics 2009-06-18 Arthur Cohen , Harold B. Sackrowitz , Minya Xu

Sequential monitoring in clinical trials is often employed to allow for early stopping and other interim decisions, while maintaining the type I error rate. However, sequential monitoring is typically described only in the context of a…

Statistics Theory · Mathematics 2012-05-29 Victoria Plamadeala , William F. Rosenberger

Matched case-control studies are commonly employed in epidemiological research for their convenience and efficiency. Analysis of secondary outcomes can yield valuable insights into biological pathways and help identify genetic variants of…

Methodology · Statistics 2026-02-24 Shanshan Liu , Guoqing Diao

We develop randomization-based tests for heterogeneous treatment effects in the presence of network interference. Leveraging the exposure mapping framework, we study a broad class of null hypotheses that represent various forms of constant…

Econometrics · Economics 2025-06-25 Julius Owusu

Evaluating treatment effect heterogeneity widely informs treatment decision making. At the moment, much emphasis is placed on the estimation of the conditional average treatment effect via flexible machine learning algorithms. While these…

Methodology · Statistics 2021-05-07 Lihua Lei , Emmanuel J. Candès

Spurious association arises from covariance between propensity for the treatment and individual risk for the outcome. For sensitivity analysis with stochastic counterfactuals we introduce a methodology to characterize uncertainty in causal…

Methodology · Statistics 2021-03-11 Brian Knaeble , Braxton Osting , Placede Tshiaba

Randomized clinical trials are considered the gold standard for estimating causal effects. Nevertheless, in studies that are aimed at examining adverse effects of interventions, such trials are often impractical because of ethical and…

Methodology · Statistics 2020-01-20 Anthony D. Scotina , Andrew R. Zullo , Robert J. Smith , Roee Gutman

Given the cost and duration of phase III and phase IV clinical trials, the development of statistical methods for go/no-go decisions is vital. In this paper, we introduce a Bayesian methodology to compute the probability of success based on…

Methodology · Statistics 2020-10-27 Ethan M. Alt , Matthew A. Psioda , Joseph G. Ibrahim

When assessing the causal effect of a binary exposure using observational data, confounder imbalance across exposure arms must be addressed. Matching methods, including propensity score-based matching, can be used to deconfound the causal…

Methodology · Statistics 2024-10-01 Ernesto Ulloa-Pérez , Marco Carone , Alex Luedtke

This is the second manuscript in a two-part series that uses diagnostic testing to understand the connection between prevalence (i.e. number of elements in a class), uncertainty quantification (UQ), and classification theory. Part I…

This paper studies inference in cluster randomized trials where treatment status is determined according to a "matched pairs" design. Here, by a cluster randomized experiment, we mean one in which treatment is assigned at the level of the…

Econometrics · Economics 2025-08-14 Yuehao Bai , Jizhou Liu , Azeem M. Shaikh , Max Tabord-Meehan

Count outcomes in longitudinal studies are frequent in clinical and engineering studies. In frequentist and Bayesian statistical analysis, methods such as Mixed linear models allow the variability or correlation within individuals to be…

Methodology · Statistics 2024-07-15 Alejandra Estefanía Patiño Hoyos , Johnatan Cardona Jiménez

Statistical inference with nonresponse is quite challenging, especially when the response mechanism is nonignorable. The existing methods often require correct model specifications for both outcome and response models. However, due to…

Methodology · Statistics 2018-09-12 Hejian Sang , Kosuke Morikawa

Many popular methods for building confidence intervals on causal effects under high-dimensional confounding require strong "ultra-sparsity" assumptions that may be difficult to validate in practice. To alleviate this difficulty, we here…

Statistics Theory · Mathematics 2019-05-06 Jelena Bradic , Stefan Wager , Yinchu Zhu

The notion of testing for equivalence of two treatments is widely used in clinical trials, pharmaceutical experiments,bioequivalence and quality control. It is essentially approached within the intersection-union (IU) principle. According…

Applications · Statistics 2018-02-07 R. Arboretti , E. Carrozzo , F. Pesarin , L. Salmaso

The likelihood ratio (LR) measures the relative weight of forensic data regarding two hypotheses. Several levels of uncertainty arise if frequentist methods are chosen for its assessment: the assumed population model only approximates the…

Applications · Statistics 2016-12-26 Giulia Cereda

Public-use survey data are an important source of information for researchers in social science and health studies to build statistical models and make inferences on the target finite population. This paper presents two general inferential…

Methodology · Statistics 2020-05-26 Puying Zhao , J. N. K. Rao , Changbao Wu

The ICH E9 addendum introduces the term intercurrent event to refer to events that happen after randomisation and that can either preclude observation of the outcome of interest or affect its interpretation. It proposes five strategies for…

Methodology · Statistics 2021-07-12 Camila Olarte Parra , Rhian M. Daniel , Jonathan W. Bartlett

Dynamical models of cognition play an increasingly important role in driving theoretical and experimental research in psychology. Therefore, parameter estimation, model analysis and comparison of dynamical models are of essential…