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From the 1 of 6 linked papers with an AI index.

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20242026
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6 papers

stat.ME2026

Factorial clinical trials in the presence and absence of plausible statistical interactions between treatment factors. A historical review of the methodological literature

Rebecca E. A. Walwyn, Pritaporn Kingkaew, Alan A. Montgomery +2

The paper reviews the methodological literature on factorial clinical trials, contrasting guidance for when statistical interactions between treatment factors are expected versus n…

stat.ME2026

Orthogonal factorial designs for trials of therapist-delivered interventions: Randomising intervention-therapist combinations to patients

Rebecca EA Walwyn, Rosemary A Bailey, Arpan Singh +2

It is recognised that treatment-related clustering should be allowed for in the sample size and analyses of individually-randomised parallel-group trials that evaluate therapist-de…

stat.ME2025

The Generalized Word Count in Two-Level Fractional Factorial Designs

Xietao Zhou, Steven G. Gilmour

Unreplicated two-level factorial designs are often used in screening experiments to determine which factors out of a large plausible set are active. A theorem regarding the general…

stat.ME2025

Pure Error REML for Analyzing Data from Multi-Stratum Designs

Steven G Gilmour, Peter Goos, Heiko Grossmann

Since the dawn of response surface methodology, it has been recommended that designs include replicate points, so that pure error estimates of variance can be obtained and used to…

stat.ME2025

-Optimal Two-Level Designs

Pi-Wen Tsai, Steven G. Gilmour

Two-level designs are widely used for screening experiments where the goal is to identify a few active factors which have major effects. Orthogonal two-level designs in which all f…

stat.ME2024

Optimal Two-Level Designs for the Baseline Parameterization

Xietao Zhou, Steven G. Gilmour

We have established the association matrix that expresses the estimator of effects under baseline parameterization, which has been considered in some recent literature, in an equiv…