Evidence map›Paper›PMID 40553468›Full record

ArticleStatistics in medicine2025

Comments on "Novel Non-Linear Models for Clinical Trial Analysis With Longitudinal Data: A Tutorial Using SAS for Both Frequentist and Bayesian Methods".

M C Donohue, P S Insel, O Langford

Abstract readLetter
In one paragraph

Article in Statistics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

M C DonohueAlzheimer's Therapeutic Research Institute, University of Southern California, San Diego, USA.ORCID https://orcid.org/0000-0001-6026-2238
P S InselDepartment of Psychiatry and Behavioral Sciences, University of California, San Francisco, USA.
O LangfordAlzheimer's Therapeutic Research Institute, University of Southern California, San Diego, USA.

Funding

The Alzheimer's Clinical Trial Consortium - Down Syndrome Network (ACTC- DSN)U24AG057437 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Paul S. Aisen, RONALD C PETERSEN · 2018 to 2026
$198.4M
NIA NIH HHS U24AG057437
6 · The paper itself

Abstract

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 over time, which can lead to bias and Type I error inflation when the assumption is violated. Even when the proportional effect assumption holds, these models are biased, and their inference is sensitive to the labeling of treatment groups. Typically, this bias favors the active group, inflates Type I error, and can result in one-sided testing. Conversely, the bias can make it more difficult to detect treatment harm, creating a safety concern.

Indexed as

Clinical Trials as TopicModels, StatisticalNonlinear DynamicsRandomized Controlled Trials as TopicBayes TheoremBiasData Interpretation, StatisticalHumansLongitudinal StudiescLDAconstrained longitudinal data analysisdisease progression modelDPMlongitudinal proportional effect modelnonlinear mixed models

Identifiers

PMID40553468
PMCPMC12186841

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.