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When the difference between treatments in a clinical trial is estimated by a difference in means, then it is well known that randomization ensures unbiassed estimation, even if no account is taken of important baseline covariates. However,…

Statistics Theory · Mathematics 2014-07-22 J. N. S. Matthews , Nuri H. Badi

The log-normal distribution is one of the most common distributions used for modeling skewed and positive data. It frequently arises in many disciplines of science, specially in the biological and medical sciences. The statistical analysis…

Methodology · Statistics 2020-01-01 Ayanendranath Basu , Abhijit Mandal , Nirian Martin , Leandro Pardo

There is a substantial literature on testing for the equality of the cumulative incidence functions associated with one specific cause in a competing risks setting across several populations against specific or all alternatives. In this…

Statistics Theory · Mathematics 2008-12-18 Hammou El Barmi , Subhash Kochar , Hari Mukerjee

Consider a pair of cumulative distribution functions $F$ and $G$, where $F$ is unknown and $G$ is a known reference distribution. Given a sample from $F$, we propose tests to detect the convexity or the concavity of $G^{-1}\circ F$ versus…

Statistics Theory · Mathematics 2025-06-25 Tommaso Lando , Mohammed Es-Salih Benjrada

In this paper, we focus on stochastic comparisons of extreme order statistics stemming from multiple-outlier scale models with dependence. Archimedean copula is used to model dependence structure among nonnegative random variables.…

Statistics Theory · Mathematics 2020-12-16 Sangita Das , Suchandan Kayal

Likelihood methods for measuring statistical evidence obey the likelihood principle while maintaining bounded and well-controlled frequency properties. These methods lend themselves to sequential study designs because they measure the…

Methodology · Statistics 2017-11-07 Jeffrey D Blume , Leena Choi

The behavior of maximum likelihood estimates (MLEs) and the likelihood ratio statistic in a family of problems involving pointwise nonparametric estimation of a monotone function is studied. This class of problems differs radically from the…

Statistics Theory · Mathematics 2009-09-29 Moulinath Banerjee

Bayesian likelihood-free methods implement Bayesian inference using simulation of data from the model to substitute for intractable likelihood evaluations. Most likelihood-free inference methods replace the full data set with a summary…

Methodology · Statistics 2020-10-16 Yinan Mao , Xueou Wang , David J. Nott , Michael Evans

The features of a logically sound approach to a theory of statistical reasoning are discussed. A particular approach that satisfies these criteria is reviewed. This is seen to involve selection of a model, model checking, elicitation of a…

Statistics Theory · Mathematics 2018-05-09 Luai Al-Labadi , Zeynep Baskurt , Michael Evans

We consider parametric hypotheses testing for multidimensional ergodic diffusion processes observed at discrete time. We propose a family of test statistics, related to the so called $\phi$-divergence measures. By taking into account the…

Statistics Theory · Mathematics 2011-11-14 Alessandro De Gregorio , Stefano Iacus

Tests for proportional hazards assumption concerning specified covariates or groups of covariates are proposed. The class of alternatives is wide: log-hazard rates under different values of covariates may cross, approach, go away. The data…

Statistics Theory · Mathematics 2020-01-20 Vilijandas Bagdonavičius , Rūta Levulienė

We derive sufficient conditions for the convex and monotonic g-stochastic ordering of diffusion processes under nonlinear g-expectations and g-evaluations. Our approach relies on comparison results for forward-backward stochastic…

Probability · Mathematics 2022-04-13 Sel Ly , Nicolas Privault

Stochastic comparisons of series and parallel systems are important in many areas of engineering, operations research and reliability analysis. These comparisons allow for the evaluation of the performance and reliability of systems under…

Statistics Theory · Mathematics 2025-06-09 CM Revathi , Rajesh Moharana , Raju Bhakta

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

Empirical likelihood approach is one of non-parametric statistical methods, which is applied to the hypothesis testing or construction of confidence regions for pivotal unknown quantities. This method has been applied to the case of…

Statistics Theory · Mathematics 2015-09-21 Fumiya Akashi , Yan Liu , Masanobu Taniguchi

We study sequential testing for a binary disease outcome when risk follows an unknown logistic model. At each round, the decision maker may either pay for a test revealing the true label or predict the outcome based on patient features and…

Machine Learning · Computer Science 2026-05-05 Tavor Z. Baharav , Spyros Dragazis , Aldo Pacchiano

The likelihood ratio test (LRT) and the related $F$ test, do not (even asymptotically) adhere to their nominal $\chi^2$ and $F$ distributions in many statistical tests common in astrophysics, thereby casting many marginal line or source…

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

Nonlinear longitudinal proportional effect models have been proposed to improve power and provide direct estimates of the proportional treatment effect in randomized clinical trials. These models assume a fixed proportional treatment effect…

Methodology · Statistics 2026-01-23 Michael C. Donohue , Philip S. Insel , Oliver Langford

Order statistics theory is applied in this paper to probabilistic robust control theory to compute the minimum sample size needed to come up with a reliable estimate of an uncertain quantity under continuity assumption of the related…

Optimization and Control · Mathematics 2008-05-13 Xinjia Chen , Kemin Zhou