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Meta-analytical models are typically formulated as a mixed-effects model where the sampling variances of the effect sizes are treated as known. In principle, such models could be fitted with standard mixed-modelling software such as the…

Mixed effects (ME) models inform a vast array of problems in the physical and social sciences, and are pervasive in meta-analysis. We consider ME models where the random effects component is linear. We then develop an efficient approach for…

This paper reviews and compares methods to assess treatment effect heterogeneity in the context of parametric regression models. These methods include the standard likelihood ratio tests, bootstrap likelihood ratio tests, and Goeman's…

Applications · Statistics 2026-02-06 Yao Chen , Sophie Sun , Konstantinos Sechidis , Cong Zhang , Torsten Hothorn , Björn Bornkamp

This contribution presents a guide to the R package multilevLCA, which offers a complete and innovative set of technical tools for the latent class analysis of single-level and multilevel categorical data. We describe the available model…

Computation · Statistics 2024-04-11 Johan Lyrvall , Roberto Di Mari , Zsuzsa Bakk , Jennifer Oser , Jouni Kuha

Estimating sample size and statistical power is an essential part of a good study design. This R package allows users to conduct power analysis based on Monte Carlo simulations in settings in which consideration of the correlations between…

Methodology · Statistics 2024-04-16 Phuc H. Nguyen , Stephanie M. Engel , Amy H. Herring

Reliability of machine learning evaluation -- the consistency of observed evaluation scores across replicated model training runs -- is affected by several sources of nondeterminism which can be regarded as measurement noise. Current…

Machine Learning · Computer Science 2023-10-10 Michael Hagmann , Philipp Meier , Stefan Riezler

The presence of outlying observations may adversely affect statistical testing procedures that result in unstable test statistics and unreliable inferences depending on the distortion in parameter estimates. In spite of the fact that the…

Methodology · Statistics 2021-04-19 Beste Hamiye Beyaztas , Soutir Bandyopadhyay , Abhijit Mandal

Robustness of linear systems with constant coefficients is considered. There exist methods and tools for analyzing the stability of systems with random or deterministic uncertainties. At the same time, there are no approaches for the…

Optimization and Control · Mathematics 2020-12-08 Andrey Tremba

This article describes the R package moodlequizR, which allows the user to easily create fully randomized quizzes and exams for Moodle, or indeed any online assessment platform that uses XML files for importing questions. In such a quiz the…

Applications · Statistics 2024-11-13 Wolfgang Rolke

Pooled testing (also known as group testing), where diagnostic tests are performed on pooled samples, has broad applications in the surveillance of diseases in animals and humans. An increasingly common use case is molecular xenomonitoring…

Computation · Statistics 2021-12-21 Angus McLure , Ben O'Neill , Helen Mayfield , Colleen Lau , Brady McPherson

SVEMnet is an R package for fitting Self-Validated Ensemble Models (SVEM) with elastic-net base learners and performing multi-response optimization in small-sample mixture-process design-of-experiments (DOE) studies with numeric,…

Computation · Statistics 2026-03-10 Andrew T. Karl

Experiments often yield non-identically distributed data for statistical analysis. Tests of hypothesis under such set-ups are generally performed using the likelihood ratio test, which is non-robust with respect to outliers and model…

Statistics Theory · Mathematics 2017-07-25 Abhik Ghosh , Ayanendranath Basu

We propose new tests for assessing whether covariates in a treatment group and matched control group are balanced in observational studies. The tests exhibit high power under a wide range of multivariate alternatives, some of which existing…

Methodology · Statistics 2019-02-28 Hao Chen , Dylan S. Small

Traditional analysis of variance (ANOVA) software allows researchers to test for the significance of main effects in the presence of interactions without exposure to the details of how the software encodes main effects and interactions to…

Methodology · Statistics 2018-01-16 Roger Levy

Linear mixed-effects models have increasingly replaced mixed-model analyses of variance for statistical inference in factorial psycholinguistic experiments. Although LMMs have many advantages over ANOVA, like ANOVAs, setting them up for…

Applications · Statistics 2017-02-14 Hannes Matuschek , Reinhold Kliegl , Shravan Vasishth , Harald Baayen , Douglas Bates

Stated choice probabilities are increasingly used in conjunction with the random-coefficient model (RCM) to describe individual preferences. They allow survey respondents to express uncertainty about the future or the incompleteness of a…

General Economics · Economics 2025-03-19 Romuald Meango

In this paper, we apply Vuong's (1989) likelihood ratio tests of non-nested models to the comparison of non-nested structural equation models. Similar tests have been previously applied in SEM contexts (especially to mixture models), though…

Applications · Statistics 2016-11-18 Edgar C. Merkle , Dongjun You , Kristopher J. Preacher

Nonlinear Mixed Effects models (NLME) models are widely used in pharmacometrics and related fields to analyze hierarchical and longitudinal data. However, as the number of parameters and random effects increases, traditional methods for…

Methodology · Statistics 2026-04-30 Mohamed Tarek , Pedro Afonso

Traditional methods for covariate adjustment of treatment means in designed experiments are inherently conditional on the observed covariate values. In order to develop a coherent general methodology for analysis of covariance, we propose a…

Methodology · Statistics 2010-01-19 James G. Booth , Walter T. Federer , Martin T. Wells , Russell D. Wolfinger

This paper introduces a likelihood ratio (LR)-type test that possesses the robustness properties of \(C(\alpha)\)-type procedures in an extremum estimation setting. The test statistic is constructed by applying separate adjustments to the…

Econometrics · Economics 2025-10-21 Jean-Marie Dufour , Purevdorj Tuvaandorj