Evidence map›Paper›PMID 28630602›Full record

ArticleMethodology : European journal of research methods for the behavioral & social sciences2016

Comparing the Performance of Improved Classify-Analyze Approaches For Distal Outcomes in Latent Profile Analysis.

John J Dziak, Bethany C Bray, Jieting Zhang, Minqiang Zhang, Stephanie T Lanza

Open access · greenAbstract read
In one paragraph

Article in Methodology : European journal of research methods for the behavioral & social sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 1 pooled it
7.0field-weighted citation impact, top 3% of its field
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

43 citing papers in PubMed, 1 synthesis or guideline pooled it, 80 citations in OpenAlex.

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  3. Latent profile analysis of self-perceptions of ageing among Chinese community-dwelling older adults.Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society · 2022
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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

5 authors at 2 institutions in 2 countries.

John J DziakThe Methodology Center, The Pennsylvania State University, University Park, PA, USA.
Bethany C BrayThe Methodology Center, The Pennsylvania State University, University Park, PA, USA.
Jieting ZhangCollege of Psychology and Sociology, Shenzhen University, Guangdong, China.
Minqiang ZhangCenter for Studies of Psychological Application, School of Psychology, South China Normal University, Guangdong, China.
Stephanie T LanzaThe Methodology Center, The Pennsylvania State University, University Park, PA, USA.
Pennsylvania State University · USSouth China Normal University · CN

Funding

THE REFINEMENT &APPLICATION OF MEDICAL DECISION MAKING IN PREVENTION SCIENCESP50DA010075 · NIDA · PENNSYLVANIA STATE UNIVERSITY-UNIV PARK · PI LANZA, STEPHANIE T · 1996 to 2014
$24.5M
Pilot, Mentoring, and Professional Development CoreP50DA039838 · NIDA · PENNSYLVANIA STATE UNIVERSITY, THE · PI COLLINS, LINDA M, LANZA, STEPHANIE T · 2015 to 2019
$13.9M
NIDA NIH HHS P50 DA010075NIDA NIH HHS P50 DA039838
6 · The paper itself

Abstract

Several approaches are available for estimating the relationship of latent class membership to distal outcomes in latent profile analysis (LPA). A three-step approach is commonly used, but has problems with estimation bias and confidence interval coverage. Proposed improvements include the correction method of Bolck, Croon, and Hagenaars (BCH; 2004), Vermunt's (2010) maximum likelihood (ML) approach, and the inclusive three-step approach of Bray, Lanza, & Tan (2015). These methods have been studied in the related case of latent class analysis (LCA) with categorical indicators, but not as well studied for LPA with continuous indicators. We investigated the performance of these approaches in LPA with normally distributed indicators, under different conditions of distal outcome distribution, class measurement quality, relative latent class size, and strength of association between latent class and the distal outcome. The modified BCH implemented in Latent GOLD had excellent performance. The maximum likelihood and inclusive approaches were not robust to violations of distributional assumptions. These findings broadly agree with and extend the results presented by Bakk and Vermunt (2016) in the context of LCA with categorical indicators.

Indexed as

classify-analyzedistal outcomelatent class analysislatent profile analysisone-stepthree-step

Identifiers

PMID28630602
PMCPMC5473653
OpenAlexW2559853966

What OpenQuestion holds

Textmetadata
LicenceTDM
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.