Cited by 1,204Psychometric Methodologies and TestingBayesian Methods and Mixture ModelsStatistical Methods and Applications

The DOI matches its Crossref record; 54 of the 56 references it cites were found in a registry or an index.

Practitioner’s Guide to Latent Class Analysis: Methodological Considerations and Common Pitfalls

Open access

Sinha, Pratik, Calfee, Carolyn S., Delucchi, Kevin L.·2021·Critical Care Medicine

DOI 10.1097/ccm.0000000000004710PMC PMC7746621

Open this paper in CoChat — free account

Abstract

Latent class analysis is a probabilistic modeling algorithm that allows clustering of data and statistical inference. There has been a recent upsurge in the application of latent class analysis in the fields of critical care, respiratory medicine, and beyond. In this review, we present a brief overview of the principles behind latent class analysis. Furthermore, in a stepwise manner, we outline the key processes necessary to perform latent class analysis including some of the challenges and pitfalls faced at each of these steps. The review provides a one-stop shop for investigators seeking to apply latent class analysis to their data.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1097/ccm.0000000000004710

Cites

54 of 54 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Silhouettes: A graphical aid to the interpretation and validation of cluster analysis
Rousseeuw, P. J. (1987) · Journal of Computational and Applied Mathematics · doi:10.1016/0377-0427(87)90125-7 · Cited by 21,392
Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
Vuong, Q. H. (1989) · Econometrica · doi:10.2307/1912557 · Cited by 5,929
The relative performance of full information maximum likelihood estimation for missing data in structural equation models
Enders, C., & Bandalos, D. (2001) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1207/s15328007sem0803_5 · Cited by 4,978
Testing the number of components in a normal mixture
Lo, Y. (2001) · Biometrika · doi:10.1093/biomet/88.3.767 · Cited by 4,640
Sample Size Requirements for Structural Equation Models: An Evaluation of Power, Bias, and Solution Propriety
Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013) · Educational and Psychological Measurement · doi:10.1177/0013164413495237 · Cited by 3,931
The problem of overfitting.
Hawkins, D. M. (2004) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci0342472 · Cited by 2,522
Acute respiratory distress syndrome
Matthay, M. A., Zemans, R. L., Zimmerman, G. A., Arabi, Y. M., Beitler, J. R., Mercat, A., Herridge, M. S., Randolph, A. G., & Calfee, C. S. (2019) · Nature Reviews Disease Primers · doi:10.1038/s41572-019-0069-0 · Cited by 2,514
Self-citation
How to Use a Monte Carlo Study to Decide on Sample Size and Determine Power
Muthén, L. K., & Muthén, B. O. (2002) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1207/s15328007sem0904_8 · Cited by 2,362
Statistical Power to Detect the Correct Number of Classes in Latent Profile Analysis
Tein, J., Coxe, S. J., & Cham, H. (2013) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2013.824781 · Cited by 2,042
Model selection and psychological theory: A discussion of the differences between the Akaike information criterion (AIC) and the Bayesian information criterion (BIC).
Vrieze, S. I. (2012) · Psychological Methods · doi:10.1037/a0027127 · Cited by 1,948

Show all 56 references

Research works printed but not linked: 3

Nylund, 2008, Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study (vol 14, pg 535, 2007)., Struct Equ Modeling, 15, 182
Tofighi, 2007, Identifying the correct number of classes in growth mixture models., Information Age, 317
McLachlan, 1987, On boostrapping the likelihood ratio test statistic for the number of components in a normal mixture., J R Stat Soc Ser C Appl Stat, 36, 318

Sorted by citations

Items 301–400 of 1,000

Person-centered insights into organizational change: Identifying and analyzing profiles using latent profile analysis
Bouckenooghe, D., Schwarz, G. M., Nguyen, P. T., & Clercq, D. D. (2025) · Australian Journal of Management · doi:10.1177/03128962251334223 · Cited by 8
Patterns in pro‐gun beliefs and weapon carrying behaviors in rural White adolescent
Beachy, S., & Liang, C. T. H. (2023) · Journal of Research on Adolescence · doi:10.1111/jora.12892 · Cited by 6
Advertisement by medical facilities as an opportunity route of APOE genetic testing in Japan: a website analysis
Sato, K., Niimi, Y., Ihara, R., Iwata, A., Ikeuchi, T., & Iwatsubo, T. (2024) · Journal of Community Genetics · doi:10.1007/s12687-024-00697-9 · Cited by 6
The Impact of Longitudinal Substance Use Patterns on the Risk of Opioid Agonist Therapy Discontinuation: A Repeated Measures Latent Class Analysis
Cui, Z., Karamouzian, M., Law, M. R., Hayashi, K., Milloy, M., & Kerr, T. H. (2023) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-023-01098-8 · Cited by 6
Clinical heterogeneity in major depressive disorder underlies comorbidity with functional disorders
Thomas, N., Gillespie, N. A., Neale, M. C., Rosmalen, J. G. M., van Loo, H. M., & Kendler, K. S. (2025) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2025.01.056 · Cited by 5
Analyzing latent categories of stress, anxiety, and depression in medical students: insights into their psychological resilience
Huang, L., Jiaming, J., Huang, B., Lyu, Y., Liu, J., Lam, L. T.-M., & Yufei, C. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1532502 · Cited by 7
Building an international precision medicine platform trial for the acute respiratory distress syndrome (ARDS): an expert consensus project report
Reddy, K., Aggarwal, N. R., Alipanah, N., Annane, D., Antcliffe, D. B., Babalis, D. S., Baillie, J. K., Beane, A., Bos, L. D. J., Burrell, A. J. C., et al. (2025) · Efficacy and Mechanism Evaluation · doi:10.3310/ttnd8896 · Cited by 6
Self-citation
Phenotype-guided risk stratification in anticoagulated atrial fibrillation patients: Cluster analysis of the Murcia AF Project III (MAFP-III)
Soler‐Espejo, E., Ramos‐Bratos, M. P., Chen, Y., González-Lozano, E., Rivera‐Caravaca, J. M., Marín, F. R., Roldán, V., & Lip, G. Y. H. (2025) · Heart Rhythm · doi:10.1016/j.hrthm.2025.09.003 · Cited by 5
What Lies beneath Diabetic Macular Edema: Latent Phenotypic Clustering and Differential Treatment Responses to Intravitreal Therapies
Cicinelli, M. V., Leonardo, B., Maiucci, G., Martino, G., Ziafati, M., Bousyf, S., Frizziero, L., Lattanzio, R., Midena, E., & Bandello, F. M. (2025) · Ophthalmology Science · doi:10.1016/j.xops.2025.100975 · Cited by 5
Profiling users and non-users of meal delivery services in Belgium using latent class analysis
Oostenbach, L. H., Keeble, M., Vanoutrive, T., Poelman, M. P., Kamphuis, C. B. M., Lippevelde, W. V., & Thornton, L. E. (2025) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-025-01827-3 · Cited by 5
Analysis of Clinical Subphenotypes in Methicillin-Resistant Staphylococcus aureus Bacteremia: A Post Hoc Analysis of the MRSA-GEIRAS-SEIMC Study
de la Villa, S., Fernández‐Hidalgo, N., Escrihuela-Vidal, F., Escudero-Sánchez, R., Cabezón, I., Boix-Palop, L., Díaz‐Pollán, B., Goikoetxea, A. J., García-Pais, M. J., Merino, L. R., et al. (2025) · Open Forum Infectious Diseases · doi:10.1093/ofid/ofaf704 · Cited by 5
Patterns, reasons and characteristics of e‐cigarette use in Australia: Findings from the 2022–2023 National Drug Strategy Household Survey
Lim, C. C. W., Sun, T., Lai, G., Hall, W., Connor, J. P., Lee, Y. Y., & Cho, A. (2025) · Addiction · doi:10.1111/add.70281 · Cited by 5
Exploring physics teachers’ views on physics education research: a case of science scepticism?
Costan, M., Costan, K., Weißbach, A., & Kulgemeyer, C. (2026) · International Journal of Science Education · doi:10.1080/09500693.2026.2629345 · Cited by 5
Managerial decision-making and AI: A taxonomy of AI collaboration orientations and strategic integration
Leszczyński, G., Gaczek, P., & Munzel, A. (2026) · Technovation · doi:10.1016/j.technovation.2026.103519 · Cited by 4
A latent class analysis of dissociative PTSD subtype among Chinese adolescents following the COVID-19 pandemic and lockdown
Bi, Y., Cao, C., Fang, R., Wang, N., Liu, P., Luo, S., Grace, E., & Wang, L. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.12.078 · Cited by 5
Classifying climate vulnerability and inequalities in India, Mexico, and Nigeria: a latent class analysis approach
Pinchoff, J., Mahapatra, B., Mishra, R., Adedimeji, A., Patel, S. K., & Regules, R. (2024) · Environmental Research Letters · doi:10.1088/1748-9326/ad1fa6 · Cited by 7
Preferences for a community pharmacy-based pre-exposure prophylaxis (PrEP) delivery program: A discrete choice experiment
Goswami, S., Bentley, J. P., Kang, M., Bhattacharya, K., & Barnard, M. (2024) · Journal of the American Pharmacists Association · doi:10.1016/j.japh.2024.102091 · Cited by 5
Latent classes of early childhood development and their predictors in Low- and middle-income countries: Results from multiple indicator cluster surveys 2010 - 2020
Sun, J., Zhang, Y., Guo, Q., Liang, M., Li, Z., & Zhang, L. (2024) · Early Childhood Research Quarterly · doi:10.1016/j.ecresq.2024.04.006 · Cited by 5
Data-driven identification of distinct pain drawing patterns and their association with clinical and psychological factors: a study of 21,123 patients with spinal pain
Chang, N. H. S., Nim, C. G., Harsted, S., Young, J. J., & O’Neill, S. F. D. (2024) · Pain · doi:10.1097/j.pain.0000000000003261 · Cited by 5
Subgroups of ICU patients identified by self-reported symptoms – A prospective multicenter study
Saltnes-Lillegård, C., Rustøen, T., Beitland, S., Puntillo, K., Thoresen, M., & Hofsø, K. (2024) · Intensive and Critical Care Nursing · doi:10.1016/j.iccn.2024.103761 · Cited by 5
Who is at risk? Applying the biopsychosocial model to explain non-violent and violent delinquency in youth
Blankenstein, N. E., Bouwmeester, S., van Haeringen, S. L., van Klink, R. T., van der Meule, L. M., & Jansen, L. M. C. (2024) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2024.101428 · Cited by 7
Tailoring age-friendly technology-enabled transportation service solutions in rural communities
Yu, J., Liu, Y., & Zhao, J. (2024) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2024.104191 · Cited by 5
Subphenotypes in Acute Respiratory Distress Syndrome: Universal Steps Toward Treatable Traits
Filippini, D. F. L., Smit, M. R., & Bos, L. D. J. (2024) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000006727 · Cited by 5
Types of depression in patients with coronary heart disease: Results from the THORESCI study
Hermans, H., Lodder, P., & Kupper, N. H. M. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.09.026 · Cited by 9
Characterizing the description of pelvic congestion syndrome pain: A latent class analysis
Patel, S. E., & Chesnut, S. R. (2024) · Phlebology The Journal of Venous Disease · doi:10.1177/02683555241287672 · Cited by 5
Patterns of Intimate Partner Violence Among Veterans: A Latent Class Analysis
Portnoy, G. A., Relyea, M., Webermann, A. R., Presseau, C., Iverson, K. M., Brandt, C., & Haskell, S. G. (2024) · Journal of Interpersonal Violence · doi:10.1177/08862605241284087 · Cited by 5
From breast cancer diagnosis to survivorship: Analyzing perioperative biopsychosocial phenotypes and their relationship to pain on long term
Groote, A. D., Dams, L., Elien, V. D. G., Schepers, J., Mertens, M. G., Groef, A. D., & Meeus, M. (2024) · Journal of Pain · doi:10.1016/j.jpain.2024.104709 · Cited by 5
Comorbidity patterns of Internet-use problems with traditional emotional and behavioral problems among Chinese adolescents: A latent class analysis
Wang, X., Mak, W. W. S., Wong, S. Y. S., & Yang, X. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2024.108551 · Cited by 5
Symptoms among patients with breast cancer undergoing endocrine therapy: Application of latent profile analysis and network analysis
He, X., Liu, C., Li, H., Wang, W., Sun, M., Lu, Y., Song, Y., & Lü, Q. (2025) · European Journal of Oncology Nursing · doi:10.1016/j.ejon.2025.102797 · Cited by 5
Patterns of substance use and associations with mental health and interpersonal violence among adolescents
Ogden, S. N., Cortez, C. A., Sterling, S., Alexeeff, S., Slama, N. E., Campbell, C. I., Satre, D. D., Asyyed, A. H., Does, M. B., Altschuler, A., et al. (2025) · Addictive Behaviors Reports · doi:10.1016/j.abrep.2025.100597 · Cited by 5
Latent cognitive profiles and their associations with instrumental activities of daily living among older adults without dementia: A United States national cross-sectional study
Li, J., Szanton, S. L., & Li, J. (2025) · The Journal of Prevention of Alzheimer s Disease · doi:10.1016/j.tjpad.2025.100162 · Cited by 5
Epigenetic and genetic profiling of comorbidity patterns among substance dependence diagnoses
Pathak, G. A., Pietrzak, R. H., Lacobelle, A., Overstreet, C. M., Wendt, F. R., Deak, J. D., Friligkou, E., Nuñez, Y. Z., Montalvo‐Ortiz, J. L., Levey, D. F., et al. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-03031-y · Cited by 5
Community and hospital-based healthcare professionals perceptions of digital advance care planning for palliative and end-of-life care: a latent class analysis
Birtwistle, J. C., Williamson, G., Relton, S. D., Bradshaw, A., Sleeman, K. E., Twiddy, M., Martin, P. M., Richards, S. H., & Allsop, M. J. (2025) · Health and Social Care Delivery Research · doi:10.3310/xcge3294 · Cited by 5
Biopsychosocial profiles following ACL reconstruction: A latent class analysis of barriers to return-to-activity
Petushek, E., Harkey, M. S., Santiago, K., Stamm, A., Baez, S., Diekfuss, J. A., Myer, G. D., & Kuenze, C. (2025) · Physical Therapy in Sport · doi:10.1016/j.ptsp.2025.08.004 · Cited by 5
Generalisability of ARDS biological subphenotype models in Asians: an international, multicentre, prospective biomarker study
Yang, H., Xia, J., Huang, X., Bai, Y., Jin, D., Nouraie, S. M., McVerry, B. J., Morris, A. M., Kitsios, G. D., Wang, C., et al. (2025) · Thorax · doi:10.1136/thorax-2025-223421 · Cited by 5
Latent class analysis-derived classification improves the cancer-specific death stratification of molecular subtyping in colorectal cancer
Zhou, W., He, M.-M., Wang, F., Xu, R., Wang, F., & Zhao, Q. (2023) · npj Precision Oncology · doi:10.1038/s41698-023-00412-w · Cited by 5
Patterns and Predictors of Low-Calorie Sweetener Consumption during Pregnancy: Findings from a National Survey
Gebremichael, B., Lassi, Z. S., Begum, M., Mittinty, M., & Zhou, S. J. (2023) · Nutrients · doi:10.3390/nu15194196 · Cited by 5
Risk profiles of adults with heavy alcohol use: Drinking patterns, behavioral and metabolic factors, health problems, and racial and ethnic disparities
Palzes, V. A., Chi, F. W., Weisner, C. M., Kline‐Simon, A. H., Satre, D. D., & Sterling, S. (2023) · Alcoholism Clinical and Experimental Research · doi:10.1111/acer.15211 · Cited by 5
Exploring the gender difference in type 2 diabetes incidence in a Swiss cohort using latent class analysis: an intersectional approach
Barbier, J. M., Amiguet, M., Vaucher, J., Lasserre, A. M., Clair, C., & Schwarz, J. (2024) · BMJ Public Health · doi:10.1136/bmjph-2023-000472 · Cited by 5
Trajectories of cognitive function among people aged 45 years and older living with diabetes in China: Results from a nationally representative longitudinal study (2011~2018)
Chen, S., Ling, Y., Zhou, F., Qiao, X., & Reinhardt, J. D. (2024) · PLoS ONE · doi:10.1371/journal.pone.0299316 · Cited by 5
Identification of the health education targeted susceptible population of tuberculosis in Ningxia, Northwest China
Ma, N., Chen, L., Ding, F., Liu, X., Li, J., & Zhao, Y. X. (2024) · Scientific Reports · doi:10.1038/s41598-024-63961-5 · Cited by 5
Impact of Provincial Income Inequality on Parenting Styles in China during COVID-19
Jin, R., Liu, N., Zhou, H., & Zhao, M. (2024) · Behavioral Sciences · doi:10.3390/bs14070587 · Cited by 5
Neurobehavioral outcomes of preterm infants: toward a holistic approach
Camerota, M., & Lester, B. M. (2024) · Pediatric Research · doi:10.1038/s41390-024-03505-9 · Cited by 5
Maximising academic achievement in online learning: the role of student-content engagement strategies and profiles
Витальевна, Г. А., & Pekeleu, M. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2024.2400072 · Cited by 5
Burn Injury Severity in Adults: Proposed Definitions Based on the National Burn Research Dataset
Heard, J., Ren, Y., Taylor, S. L., Sen, S., Palmieri, T. L., Romanowski, K. S. S., & Greenhalgh, D. (2024) · Journal of Burn Care & Research · doi:10.1093/jbcr/irae186 · Cited by 5
Association of Dietary Patterns, C-Reactive Protein, and Risk of Obesity Among Children Aged 9–17 Years in Guangzhou, China: A Cross-Sectional Mediation Study
Su, Z., Zeng, C., Huang, J., Luo, S., Guo, J., Fu, J., Zhang, W., Zhang, Z., Zhang, B., & Li, Y. (2024) · Nutrients · doi:10.3390/nu16223835 · Cited by 5
Typology of Social Participation and Network and Health in Older Adults: Results From the Canadian Longitudinal Study on Aging
Deslauriers, V., & Levasseur, M. (2025) · Journal of Aging and Health · doi:10.1177/08982643241311632 · Cited by 5
Associations Among Childhood Household Income, Latent Classes of Early Adverse Childhood Experiences, and Adolescent Mental Health
Moore, C. R., Veliz, P. T., Herrenkohl, T. I., Miller, A. L., Pilkauskas, N., & Stoddard, S. A. (2025) · Issues in Mental Health Nursing · doi:10.1080/01612840.2025.2490286 · Cited by 5
Psychological Resilience Mediates the Association Between Childhood Maltreatment and Self-Harm Phenotype in Chinese Early Adolescents
Li, Y., Li, Y., He, Y., Chen, S.-S., Chang, J.-J., Yuan, M., Cao, L., Wang, S.-J., Wang, G., & Su, P. (2022) · Child Psychiatry & Human Development · doi:10.1007/s10578-022-01471-z · Cited by 5
Chinese parents’ caregiving ability for children with haematological malignancies: A latent class analysis
Wang, J., Bi, X., Wang, J., Gu, Y., Zheng, X., Wang, Y., Wu, H., Yang, Q., Ma, L., Liu, F., et al. (2022) · Nursing Open · doi:10.1002/nop2.1218 · Cited by 5
Latent Class Analysis to Identify Subgroups in Clinical Research
Bailly, S., & Dey, T. (2026) · CHEST Journal · doi:10.1016/j.chest.2025.07.4085 · Cited by 5
Patterns of Internalizing Problems, Substance Use and Cognitive Flexibility Before and After Naturalistic Psilocybin Use: A Repeated Measures Latent Profile Analysis
Richard, J., Scott, J., Nayak, S. M., Sepeda, N. D., Lowe, M. X., Jackson, H., & Garcia‐Romeu, A. (2025) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-025-01489-z · Cited by 4
On the Use of Elbow Plot Method for Class Enumeration in Factor Mixture Models
Şen, S., & Cohen, A. S. (2025) · Applied Psychological Measurement · doi:10.1177/01466216251344288 · Cited by 4
Characterizing Prenatal Exposure to Contemporary and Emerging Chemicals in a Prospective Cohort of Pregnant Women in Atlanta, Georgia
Ortlund, K., Dunlop, A. L., Barr, D. B., Liang, D., Tan, Y., Buckley, J. P., Kannan, K., Chandler, M., Ren, M., & Eick, S. M. (2025) · Environment & Health · doi:10.1021/envhealth.5c00347 · Cited by 4
Female Offending Trajectories: A Systematic Review
Coles, C. E., Wickersham, A., Lankester, M., Jolliffe, D., Blackwood, N., & Dickson, H. (2026) · Journal of Developmental and Life-Course Criminology · doi:10.1007/s40865-026-00295-y · Cited by 5
Identification of echocardiographic subgroups in patients with coronary heart disease combined with heart failure based on latent variable stratification
Du, Y., Yuan, N., Yan, J., Han, G., Hu, X., Zhang, Y., & Tian, J. (2022) · International Journal of Cardiology · doi:10.1016/j.ijcard.2022.11.038 · Cited by 4
Identification and Prediction of Clinical Phenotypes in Hospitalized Patients With COVID-19: Machine Learning From Medical Records
Velez, T., Wang, T., Garibaldi, B. T., Singman, E. L., & Koutroulis, I. (2023) · JMIR Formative Research · doi:10.2196/46807 · Cited by 4
Identifying latent classes of suicidal ambivalence: Associations with suicide risk correlates and outcomes
Mitchell, S. M., Marvin, C., Mitaj, D., & Rogers, M. L. (2024) · Suicide and Life-Threatening Behavior · doi:10.1111/sltb.13111 · Cited by 4
Majority expectations regarding immigrant acculturation in Belgium: A person-centered, domain-specific approach
Árnadóttir, K., & Meeusen, C. (2024) · International Journal of Intercultural Relations · doi:10.1016/j.ijintrel.2024.102038 · Cited by 4
Stress coping and resilience of frontline nurses under the emergency infectious disease pandemic: A latent class analysis
Yeh, Y.-C., Sheng, W., Pan, M., Liu, H.-Y., Liu, C., & Chiou, P. (2024) · Applied Nursing Research · doi:10.1016/j.apnr.2024.151857 · Cited by 5
A latent class analysis of co-occurring insomnia and anxiety among Chinese pregnant women
Liu, S., Huang, M., Tao, J., Wen, D., Ping, Z., Zhang, F. Y., & Li, M. (2024) · Journal of Psychosomatic Obstetrics & Gynecology · doi:10.1080/0167482x.2024.2437391 · Cited by 4
Multimorbidity latent classes in relation to 11-year mortality, risk factors and health-related quality of life in Malaysia: a prospective health and demographic surveillance system study
Tan, M. M. C., Hanlon, C., Terrera, G. M., Benaglia, T., Ismail, R., Mohan, D., Konkoth, A. B., Reidpath, D. D., Pinho, P. J. D. M. R., Allotey, P. A., et al. (2025) · BMC Medicine · doi:10.1186/s12916-024-03796-z · Cited by 4
Observational and Genetic Analyses of Traumatic Experiences and Endometriosis
Koller, D., Løkhammer, S., Goroshchuk, O., Denner, V., Stiltner, B., Mitjans, M., He, J., Taylor, H. S., Lawn, R. B., Koenen, K. C., et al. (2025) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2024.4694 · Cited by 4
Identification of Symptom Profiles in Prostate Cancer Survivors
An, J., Blair, C. K., Lin, Y., Lu, S., Arap, W., Saraiya, B., Irwin, M. R., & Kinney, A. Y. (2025) · Oncology nursing forum · doi:10.1188/25.onf.137-150 · Cited by 4
Electronic device usage pattern is associated with sleep disturbances in adolescents: a latent class analysis
Lin, Q.-W., Wei, S.-H., Wu, Y.-X., Wei, S., & Lin, Y. (2025) · European Journal of Pediatrics · doi:10.1007/s00431-025-06065-0 · Cited by 4
Characteristics and influencing factors of fear of cancer recurrence among family caregivers of breast cancer patients: a latent class analysis
Liu, W., Li, W., Deng, L., Luo, X., Tan, Y., Xiang, J., Wu, Y., Hu, Y., Sun, H., & Yang, Y. (2025) · BMC Nursing · doi:10.1186/s12912-025-02964-7 · Cited by 4
Socioeconomic Status, Modifiable Factors, and Risk of Microvascular Complications in Individuals With Type 2 Diabetes: A Cohort Study From the UK Biobank
Li, Y., You, Q., Fan, M., Wei, L., Zeng, J., Chen, B., Wang, J., & Xu, S. (2025) · Journal of Diabetes · doi:10.1111/1753-0407.70079 · Cited by 4
Identifying high-risk groups for self-harm in adolescents using the Avon Longitudinal Study of Parents and Children (ALSPAC): a cross-cohort comparison latent class analysis study
McEvoy, D., Brannigan, R., Healy, C., Mongan, D., & Clarke, M. C. (2025) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-025-02702-z · Cited by 4
Natural subgroups of tension‐type headache: A population‐based study
Lee, W., Heo, S., & Chu, M. K. (2025) · Headache The Journal of Head and Face Pain · doi:10.1111/head.14950 · Cited by 4
Identifying clinical phenotype clusters in patients with coronary artery disease
Holtrop, J., Lim, C.-E., Uijl, A., Ueda, P., Jernberg, T., van der Meer, M. G., van der Harst, P., Kraaijeveld, A. O., Balder, J.-W., Hageman, S. H. J., et al. (2025) · Heart · doi:10.1136/heartjnl-2025-325740 · Cited by 4
Enhanced mental health literacy: A potential solution to mitigate the link between health risk behaviors and multiple psychological symptoms among Chinese adolescents
Wang, B., Huang, N., Chen, C., Jiang, Q., Zhang, M., Hu, B., Zhu, S., & Guo, J. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.119668 · Cited by 4
Cross‐cultural variations in executive function impairments among children with attention deficit/hyperactivity disorder
Zhang, D., Amran, A. S., Qin, Y., Jiang, H., Sun, L., Bellgrove, M. A., & Johnstone, S. J. (2025) · JCPP Advances · doi:10.1002/jcv2.70032 · Cited by 4
Identifying subphenotypes of patients undergoing post‐operative delirium assessment
Bowman, E. M. L., McAuley, D. F., McGuinness, B., Passmore, A. P., Beverland, D., Zetterberg, H., Schott, J. M., Heslegrave, A., Veleva, E., Laban, R., et al. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.70516 · Cited by 4
Phenotypes of patients with symptomatic lumbar spinal stenosis presenting for nonoperative care: baseline data from the Lumbar Stenosis Prognostic Subgroups for Personalizing Care and Treatment Study (PROSPECTS)
Rundell, S. D., Meier, E. N., Jarvik, J. G., Friedly, J. L., Horn, M. E., Suri, P., Cizik, A. M., Heagerty, P. J., Johnston, S. K., Fillipo, R., et al. (2025) · Pain Medicine · doi:10.1093/pm/pnaf099 · Cited by 4
Mathematics-related teacher identity profiles of preservice elementary school teachers and middle school mathematics teachers: A latent class analysis
Arslan, O., Çelikdemir, K., & Haser, Ç. (2025) · Teaching and Teacher Education · doi:10.1016/j.tate.2025.105159 · Cited by 4
Odds Ratio Product as a Biological Marker of Phenotypes of Insomnia
Lambing, K. A., Guadagni, V., Gerardy, B., Bender, A. M., Younes, M. K., & Bastien, C. (2025) · Journal of Sleep Research · doi:10.1111/jsr.70169 · Cited by 4
Distinct and reproducible neurocognitive profiles in stable diffuse glioma: A data-driven approach to understanding cognitive heterogeneity
Gorter, M., Röttgering, J. G., Belgers, V., van Lingen, M. R., Hamer, P. C. D. W., Douw, L., & Klein, M. (2025) · Neuro-Oncology · doi:10.1093/neuonc/noaf197 · Cited by 4
Municipal Oral Healthcare Coverage and Dental Caries among Brazilian Children
Piovesan, É. T. D. A., & Bernabé, E. (2025) · Caries Research · doi:10.1159/000548560 · Cited by 4
Characterizing Violence Intervention Street Outreach Participants and Service Dosage: Implications for Measurement and Evaluation
Ross, M. C., Burtner, S., & Papachristos, A. V. (2025) · INQUIRY The Journal of Health Care Organization Provision and Financing · doi:10.1177/00469580251360634 · Cited by 4
The association between chronic pain and the clustering of menopausal symptoms: Evidence from a British birth cohort study
Borra, C., & Hardy, R. (2025) · Maturitas · doi:10.1016/j.maturitas.2025.108756 · Cited by 4
Identification of clinical phenotypes in Behçet's syndrome using latent class analysis: a step toward precision medicine
Chadli, S., Maamar, M., Abouqal, R., Ammouri, W., Tazi, Z. M., & Harmouche, H. (2025) · Clinical and Experimental Rheumatology · doi:10.55563/clinexprheumatol/3dhh59 · Cited by 4
Latent profile analysis of core competency in intravenous therapy among Chinese clinical nurses: a multicenter cross-sectional study
Li, S., Li, Y., Ye, Q., Zhang, Z., Song, J., Huang, D., Wen, X., & Huang, Q. (2025) · BMC Nursing · doi:10.1186/s12912-025-04007-7 · Cited by 4
Retention and effectiveness of group interpersonal psychotherapy (IPT-G) to treat depression at scale in Uganda and Zambia
Assefa, F. B., Tanner, L., Kim, H., Platais, I., Tindyebwa, C. M., Kasujja, R., & Bershteyn, A. (2025) · BMJ Global Health · doi:10.1136/bmjgh-2024-018369 · Cited by 4
Perceived infertility-related stress, partner attachment, and psychological distress among women undergoing in-vitro fertilization treatment: a latent profile and mediation analysis
Liu, D., Hu, S., Fu, B., Yang, Q., Huang, R., Huang, J., & Shen, Q. (2025) · BMC Women s Health · doi:10.1186/s12905-025-04172-6 · Cited by 4
Profiles and Predictors of Neurodevelopmental Outcome at 5–6 Years in Children With a History of Acute Provoked Neonatal Seizures
Glass, H. C., Numis, A. L., Soul, J. S., Wusthoff, C. J., Lemmon, M. E., Benedetti, G. M., Chu, C. J., Massey, S. L., Thomas, C., Anwar, T., et al. (2026) · Annals of Neurology · doi:10.1002/ana.78100 · Cited by 4
Where heat adaptation is needed most - An open-source approach to developing a transferable heat risk index for urban planning
Rupp, S., Leichtle, T., Beck, C., & Hiete, M. (2026) · Urban Climate · doi:10.1016/j.uclim.2025.102769 · Cited by 4
Safety and Exposure in Transparent School Interiors: Patterned User Perceptions of Glass
Altenburger, E., & Russell, L. T. (2023) · Journal of Interior Design · doi:10.1177/10717641231202738 · Cited by 4
A Research-Based Literacy Instruction MTSS for Juvenile Correctional Facilities
Houchins, D. E., Lambert, R. G., Henrich, C. C., & Gagnon, J. C. (2024) · Behavioral Disorders · doi:10.1177/01987429231225633 · Cited by 4
Exploring subgroups of acceptance prediction for e-mental health among psychotherapists-in-training: a latent class analysis
Staeck, R., Stüble, M., & Drüge, M. (2024) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2024.1296449 · Cited by 4
Latent class analysis of chest CT abnormalities to define subphenotypes in patients with MPO-ANCA-positive microscopic polyangiitis
Gu, Y., Zhang, T., Peng, M., Han, Y., Zhang, W., & Shi, J. (2024) · Respiratory Medicine · doi:10.1016/j.rmed.2024.107613 · Cited by 4
Characterization of Latent Classes of Early Preadolescents from Their Reports of Victimization and Bullying – A Latent Class Analysis
Cárcamo, M., Cumsille, P. E., & Gaete, J. (2024) · International Journal of Bullying Prevention · doi:10.1007/s42380-024-00247-4 · Cited by 5
Latent Profiles of Disordered Eating Among Veterans: Associations With Mental Health Concerns
Klimek, P., Yalch, M. M., & Maguen, S. (2024) · Women s Health Issues · doi:10.1016/j.whi.2024.03.002 · Cited by 4
A multi-method assessment of emotional processes predicting longitudinal anxiety symptom trajectories in an adolescent clinical sample
Cetinkaya, D., DeCaro, S. A., Turnamian, M. R., Poon, J. A., Kleiman, E. M., & Liu, R. T. (2024) · Journal of Mood and Anxiety Disorders · doi:10.1016/j.xjmad.2024.100071 · Cited by 4
Predicting longitudinal changes in patterns of tobacco and nicotine product use among adolescents: A Latent Transition Analysis based on the X:IT study
Lund, L., Andersen, S., Ritz, C., & Bast, L. S. (2024) · Social Science & Medicine · doi:10.1016/j.socscimed.2024.117029 · Cited by 4
Latent class analysis and longitudinal development trajectory study of psychological distress in patients with stroke: a study protocol
Guo, Y., Ming, Z., Yan, X., Liu, Y., & Wang, L. (2024) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2024.1326988 · Cited by 4
Childhood conditions and mental health among youth and young adults in Greenland: a latent class analysis
Ottendahl, C. B., Bjerregaard, P., Svartá, D. L., Seidler, I. K., Olesen, I., Nielsen, M. S., & Larsen, C. V. L. (2024) · International Journal of Circumpolar Health · doi:10.1080/22423982.2024.2400397 · Cited by 4
Patterns of pain medication usage and self-reported pain in older Irish adults with osteoarthritis: A latent class analysis of data from the Irish Longitudinal Study on Ageing
French, H. P., Cunningham, J., Bennett, K., Cadogan, C. A., Clyne, B., Doyle, F., Moriarty, F., Ryan, J. M., Smith, S. M., & Passos, V. L. (2024) · BMC Musculoskeletal Disorders · doi:10.1186/s12891-024-07854-8 · Cited by 4
Gender differences in the association between inter-generational interaction and depressive symptoms among Chinese older adults
Li, D., Yang, J., & Zhu, L. (2024) · BMC Geriatrics · doi:10.1186/s12877-024-05345-y · Cited by 4
Work‐Related Stress and Behavioural Correlates of Lower Urinary Tract Symptom Profiles in Female Nurses: A Latent Class Analysis Based on the Nurse Urinary Related Health Study
Gao, J., Xu, D., Wu, C., Li, M., Ren, J., Rao, Y., & Wang, K. (2024) · Journal of Nursing Management · doi:10.1155/2024/7318901 · Cited by 4
Clinical and neurocognitive profiles of a combined clinical high risk for psychosis and clinical control sample: latent class analysis
Stüble, M., Schultze‐Lutter, F., Kaess, M., Franscini, M., Traber‐Walker, N., Walger, P., SCHIMMELMANN, B. G., Vogeley, K. T., Kambeitz, J. P., Kindler, J., et al. (2024) · BJPsych Open · doi:10.1192/bjo.2024.815 · Cited by 4

Authors: Sinha, P., Calfee, C. S., & Delucchi, K. L.
Affiliations: University of California, San Francisco (US)
ORCID: Sinha, Pratik
Calfee, Carolyn S.
Delucchi, Kevin L.
Venue: Critical Care Medicine
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2020-11-09
Volume: 49
Issue: 1
Pages: e63-e79
ISSN: 0090-3493 (ISSN-L)
DOI: 10.1097/ccm.0000000000004710
PMC: PMC7746621
OpenAlex: W3102547229
Cited by: 1,204
References: 56
Citations by year: 2026: 386 · 2025: 382 · 2024: 290 · 2023: 98 · 2022: 35 · 2021: 13
FWCI: 7.14
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Critical Care Medicine (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
eScholarship (California Digital Library) (submittedVersion)
Funders: National Heart, Lung, and Blood Institute (R35HL140026)
National Institute of General Medical Sciences (T32GM008440)
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Methods and Mixture Models
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Keywords: latent class analysis, clustering, stochastic modeling, statistical inference, intensive care, respiratory medicine, methodological pitfalls, data analysis pipeline
MeSH terms: Latent Class Analysis, Data Interpretation, Statistical, Humans, Statistics as Topic

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Practitioner’s Guide to Latent Class Analysis: Methodological Considerations and Common Pitfalls

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks