ArticleJournal of the American Statistical Association2024
Projection Test for Mean Vector in High Dimensions.
Article in Journal of the American Statistical Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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.
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Who cites it
3 citing papers in PubMed.
- Power-enhanced two-sample mean tests for high-dimensional microbiome compositional data.Biometrics · 2025Article
- A Novel Approach of High Dimensional Linear Hypothesis Testing Problem.Journal of the American Statistical Association · 2025Article
- Omnibus test for restricted mean survival time based on influence function.Statistical methods in medical research · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
This paper studies the projection test for high-dimensional mean vectors via optimal projection. The idea of projection test is to project high-dimensional data onto a space of low dimension such that traditional methods can be applied. We first propose a new estimation for the optimal projection direction by solving a constrained and regularized quadratic programming. Then two tests are constructed using the estimated optimal projection direction. The first one is based on a data-splitting procedure, which achieves an exact
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Registered trials
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.