Evidence map›Paper›PMID 41536944›Full record

ArticleStat2025

Power and sample size calculation of two-sample projection-based testing for sparsely observed functional data.

Salil Koner, Sheng Luo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Stat, 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

2 authors.

Salil KonerDepartment of Biostatistics and Bioinformatics, Duke University, North Carolina, USA.
Sheng LuoDepartment of Biostatistics and Bioinformatics, Duke University, North Carolina, USA.

Funding

Research Education Component CoreP30AG072958 · NIA · DUKE UNIVERSITY · PI GWENN A GARDEN, Heather E. Whitson · 2021 to 2026
$24.1M
Integrative modeling and dynamic prediction of Alzheimer's diseaseR01AG064803 · NIA · DUKE UNIVERSITY · PI LUO, SHENG · 2020 to 2024
$2.3M
Integrative modeling and dynamic prediction of Alzheimer's diseaseR56AG064803 · NIA · DUKE UNIVERSITY · PI LUO, SHENG · 2019 to 2019
$483k
NIA NIH HHS P30 AG072958NIA NIH HHS R01 AG064803NIA NIH HHS R56 AG064803
6 · The paper itself

Abstract

Projection-based testing for mean trajectory differences in two groups of irregularly and sparsely observed functional data has garnered significant attention in the literature because it accommodates a wide spectrum of group differences and (non-stationary) covariance structures. This article presents the derivation of the theoretical power function and the introduction of a comprehensive power and sample size (PASS) calculation toolkit tailored to the projection-based testing method developed by Wang

Indexed as

Azilect trialHypothesis testingLongitudinal dataSparse Functional data

Identifiers

PMID41536944
PMCPMC12799244

What OpenQuestion holds

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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.