Evidence map›Paper›PMID 37002429›Full record

ArticlePsychometrika2023

Rotation to Sparse Loadings Using

Xinyi Liu, Gabriel Wallin, Yunxiao Chen, Irini Moustaki

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Psychometrika, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

4 authors.

Xinyi LiuDepartment of Statistics, London School of Economics and Political Science, Columbia House, Room 5.16, Houghton Street, London, WC2A 2AE, UK.
Gabriel WallinDepartment of Statistics, London School of Economics and Political Science, Columbia House, Room 5.16, Houghton Street, London, WC2A 2AE, UK.
Yunxiao ChenDepartment of Statistics, London School of Economics and Political Science, Columbia House, Room 5.16, Houghton Street, London, WC2A 2AE, UK. y.chen186@lse.ac.uk.ORCID 0000-0002-7215-2324
Irini MoustakiDepartment of Statistics, London School of Economics and Political Science, Columbia House, Room 5.16, Houghton Street, London, WC2A 2AE, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Researchers have widely used exploratory factor analysis (EFA) to learn the latent structure underlying multivariate data. Rotation and regularised estimation are two classes of methods in EFA that they often use to find interpretable loading matrices. In this paper, we propose a new family of oblique rotations based on component-wise

Indexed as

AlgorithmsComputer SimulationPsychometricsanalytic rotationcomponent loss functionconfidence intervalmodel selectionregularised estimation

Identifiers

PMID37002429
PMCPMC10188427

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.