ArticleHealth services & outcomes research methodology2014
ADDRESSING CONFOUNDING WHEN ESTIMATING THE EFFECTS OF LATENT CLASSES ON A DISTAL OUTCOME.
Article in Health services & outcomes research methodology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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.
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
15 citing papers in PubMed.
- The correlation between latent types of emotional processing, physical exercise and aggressive behavior among middle school students: a study based on latent profile analysis.Frontiers in psychology · 2026Article
- Adolescent Gender Beliefs in India: Does Mothers' Empowerment Matter?Social science research · 2025Article
- Evaluating sensitivity to classification uncertainty in latent subgroup effect analyses.BMC medical research methodology · 2022Article
- Mental Health Beliefs, Access, and Engagement with Military Sexual Trauma-Related Mental Health Care.Journal of general internal medicine · 2022Article
- Longitudinal Patterns of Material Hardship among US Families.Social indicators research · 2022Article
- Profiling Disease and Economic Burden in CRSwNP Using Machine Learning.Journal of asthma and allergy · 2022Article
- Causal Inference in Radiomics: Framework, Mechanisms, and Algorithms.Frontiers in neuroscience · 2022Article
- Relative and absolute wealth mobility since birth in relation to health and human capital in middle adulthood: An analysis of a Guatemalan birth cohort.SSM - population health · 2021Article
- Childhood patterns of overweight and wheeze and subsequent risk of current asthma and obesity in adolescence.Paediatric and perinatal epidemiology · 2021Article
- Separating Algorithms From Questions and Causal Inference With Unmeasured Exposures: An Application to Birth Cohort Studies of Early Body Mass Index Rebound.American journal of epidemiology · 2021Article
- Ensuring Causal, Not Casual, Inference.Prevention science : the official journal of the Society for Prevention Research · 2019Article
- Inverse Propensity Score Weighting with a Latent Class Exposure: Estimating the Causal Effect of Reported Reasons for Alcohol Use on Problem Alcohol Use 16 Years Later.Prevention science : the official journal of the Society for Prevention Research · 2019Article
- Coping profiles and subjective well-being among people living with HIV: less intensive coping corresponds with better well-being.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2017Article
- Latent Classes of Adolescent Sexual and Romantic Relationship Experiences: Implications for Adult Sexual Health and Relationship Outcomes.Journal of sex research · 2016Article
- Patterns of relationship and sexual behaviors in Mexican adolescents and associations with well-being: A latent class approach.Journal of adolescence · 2015Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Confounding is widely recognized in settings where all variables are fully observed, yet recognition of and statistical methods to address confounding in the context of latent class regression are slowly emerging. In this study we focus on confounding when regressing a distal outcome on latent class; extending standard confounding methods is not straightforward when the treatment of interest is a latent variable. We describe a recent 1-step method, as well as two 3-step methods (modal and pseudoclass assignment) that incorporate propensity score weighting. Using simulated data, we compare the performance of these three adjusted methods to an unadjusted 1-step and unadjusted 3-step method. We also present an applied example regarding adolescent substance use treatment that examines the effect of treatment service class on subsequent substance use problems. Our simulations indicated that the adjusted 1-step method and both adjusted 3-step methods significantly reduced bias arising from confounding relative to the unadjusted 1-step and 3-step approaches. However, the adjusted 1-step method performed better than the adjusted 3-step methods with regard to bias and 95% CI coverage, particularly when class separation was poor. Our applied example also highlighted the importance of addressing confounding - both unadjusted methods indicated significant differences across treatment classes with respect to the outcome, yet these class differences were not significant when using any of the three adjusted methods. Potential confounding should be carefully considered when conducting latent class regression with a distal outcome; failure to do so may results in significantly biased effect estimates or incorrect inferences.
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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.