Construction of multilevel statistical models in health research: Foundations and generalities
Abstract
This topic review aims to present a global vision of multilevel analysis models’ applicability to health research, explaining its theoretical, methodological, and statistical foundations. We describe the basic steps to build these models and examples of their application according to the data hierarchical structure.
It ir worth noticing that before using these models, researchers must have a rationale for needing them, and a statistical evaluation accounting for the variance percentage explained by the observations grouping effect.
The requirements to conduct this type of analysis depends on special conditions such as the type of variables, the number of units per level, or the type of hierarchical structure.
We conclude that multilevel analysis models are a useful tool to integrate information, considering the complexity of the relationships and interactions involved in most health conditions, including the loss of independence between observation units.
Downloads
References
De la Cruz F. Modelos multinivel. Rev Per Epidemiol. 2008;12:1-8.
Diez-Roux AV. Multilevel analysis in public health research. Annu Rev Public Health. 2000;21:171-92. https://doi.org/10.1146/annurev.publhealth.21.1.171
Usami S. Generalized sample size determination formulas for experimental research with hierarchical data. Behav Res Methods. 2014;46:346-56. https://doi.org/10.3758/s13428-013-0387-1
Rasbash J, Steele F, Browne WJ, Goldstein H. University of Bristol, Centre for Multilevel Modelling MLwiN, version 3.07. Fecha de consulta: 1º de agosto de 2023. Disponible en: https://www.bristol.ac.uk/cmm/media/software/mlwin/downloads/manuals/3-07/manual-web.pdf
Diez-Roux AV. La necesidad de un enfoque multinivel en epidemiología. Region Soc. 2008;20:77-91.
Fisher AJ, Medaglia JD, Jeronimus BF. Lack of group-to-individual generalizability is a threat to human subjects research. Proc Natl Acad Sci USA. 2018;115:E6106-15. https://doi.org/10.1073/pnas.1711978115
University of Bristol. Centre for Multilevel Modelling. What are multilevel models and why should I use them? Fecha de consulta: 16 de noviembre de 2022. Disponible en: http://www.bristol.ac.uk/cmm/learning/multilevel-models/what-why.html
Damtie Y, Kefale B, Yalew M, Arefaynie M, Adane B. Multilevel analysis of determinants of polygyny among married men in Ethiopia. BMC Glob Public Health. 2021;21:1677. https://doi.org/10.1186/s12889-021-11701-z
Dessie ZG, Zewotir T, Mwambi H, North D. Multivariate multilevel modeling of quality of life dynamics of HIV infected patients. Health Qual Life Outcomes. 2020;18:80. https://doi.org/10.1186/s12955-020-01330-2
Hagadorn JI, Shaffer ML. Hierarchical data structures and multilevel modeling. J Pediatr. 2019;212:250-1. https://doi.org/10.1016/j.jpeds.2019.05.042
Huang F. Multilevel modeling myths. Sch Psychol Q. 2018;33:492-9. https://doi.org/10.1037/spq0000272
Ntani G, Inskip H, Osmond C, Coggon D. Consequences of ignoring clustering in linear regression. BMC Med Res Methodol. 2021;21:139. https://doi.org/10.1186/s12874-021-01333-7
Mumper M. American Psycological Association. 2017. Multilevel modelling. Fecha de consulta: 16 de noviembre de 2022. Disponible en: https://www.apa.org/science/about/psa/2017/01/multilevel-modelling
University of Bristol. Centre for Multilevel Modelling. Multilevel models: An introduction and FAQs. Fecha de consulta: 15 de noviembre de 2022. Disponible en: http://www.bristol.ac.uk/cmm/learning/multilevel-models/
Barker KM, Dunn EC, Richmond TK, Ahmed S, Hawrilenko M, Evans CR. Cross-classified multilevel models (CCMM) in health research: A systematic review of published empirical studies and recommendations for best practices. SSM Popul Health. 2020;12. https://doi.org/10.1016/j.ssmph.2020.100661
Finch H, Bolin JE, Kelley K. Multilevel modeling using R. 2.a edition. Boca Raton: Chapman and Hall/CRC; 2019. p. 252.
University of Bristol. Centre for Multilevel Modelling. Random intercept models. Fecha de consulta: 27 de diciembre de 2021. Disponible en: https://www.bristol.ac.uk/cmm/learning/videos/random-intercepts.html
Speed TP. Restricted maximum likelihood: Overview. En: Balakrishnan N, Colton T, Everitt B, Piegorsch W, Ruggeri F, Teugels JL, editores. Wiley StatsRef: Statistics Reference Online. Wiley; 2014. https://doi.org/10.1002/9781118445112.stat01451
Bolin JH, Finch WH, Stenger R. Estimation of random coefficient multilevel models in the context of small numbers of level 2 clusters. Educ Psychol Meas. 2019;7:217-48. https://doi.org/10.1177/0013164418773494
Webster TF, Hoffman K, Weinberg J, Vieira V, Aschengrau A. Community- and individuallevel socioeconomic status and breast cancer risk: Multilevel modeling on Cape Cod, Massachusetts. Environ Health Perspect. 2008;116:1125-9. https://doi.org/10.1289/ehp.10818
Austin PC, Wagner P, Merlo J. The median hazard ratio: A useful measure of variance and general contextual effects in multilevel survival analysis. Stat Med. 2017;36:928-38. https://doi.org/10.1002/sim.7188
Austin PC, Stryhn H, Leckie G, Merlo J. Measures of clustering and heterogeneity in multilevel Poisson regression analyses of rates/count data. Stat Med. 2018;37:572-89. https://doi.org/10.1002/sim.7532
Merlo J, Chaix B, Ohlsson H, Beckman A, Johnell K, Hjerpe P, et al. A brief conceptual tutorial of multilevel analysis in social epidemiology: Using measures of clustering in multilevel logistic regression to investigate contextual phenomena. J Epidemiol Community Health. 2006;60:290-7. https://doi.org/10.1136/jech.2004.029454
Ballesteros SM, Moreno-Montoya J. Factores individuales y departamentales asociados con la prevalencia de limitación funcional entre ancianos colombianos: un análisis multinivel. Cad Saúde Pública. 2018;34:12. https://doi.org/10.1590/0102-311X00163717
Dedrick RF, Ferron JM, Hess MR, Hogarty KY, Kromrey JD, Lang TR, et al. Multilevel modeling: A review of methodological issues and applications. Rev Educ Res. 2009;79:69-102. https://doi.org/10.3102/0034654308325581
Catalán-Reyes MJ, Galindo-Villardón MP. Utilización de los modelos multinivel en investigación sanitaria. Gac Sanit. 2003;17(Supl.3):35-52.
Peugh JL. A practical guide to multilevel modeling. J Sch Psychol. 2010;48:85-112. https://doi.org/10.1016/j.jsp.2009.09.002
Osorio AM, Romero GA, Bonilla H, Aguado LF. Socioeconomic context of the community and chronic child malnutrition in Colombia. Rev Saúde Pública. 2018;52:1-12. https://doi.org/10.11606/S1518-8787.2018052000394
Gabriëlle I, Jongmans M. Intra-class correlation testing to examine Intra-group differences [Bachelor thesis]. Enschede: University of Twente; 2021.
Yamana H. Introduction to multilevel analysis. Ann Clin Epidemiol. 2021;3:5-9. https://doi.org/10.37737/ace.3.1_5
Killip S, Mahfoud Z, Pearce K. What is an intracluster correlation coefficient? Crucial concepts for primary care researchers. Ann Fam Med. 2004;2:204-8. https://doi.org/10.1370/afm.141
Ramos-Rodríguez FJ, Lara Porras AM, Molina-Muñoz D. Competencia matemática de los estudiantes andaluces: un análisis multinivel de la encuesta PISA 2015. Pi-InnovaMath. 2019;2. https://doi.org/10.5944/pim.2.2019.24130
Alarcón R, Blanca MJ, Arnau J, Bono R. Modelado jerárquico por pasos: análisis multinivel del estrés cotidiano en adolescentes. Rev Mex Psicol. 2015;32:12433.
Vrieze SI. Model selection and psychological theory: A discussion of the differences between the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). Psychol Methods. 2012;17:228-43. https://doi.org/10.1037/a0027127
Oliver JC, Rosel J, Jara P. Modelos de regresión multinivel: aplicación en psicología escolar. Psicothema. 2000;12:487-94.
Kim S, Jeong Y, Hong S. The impact of ignoring a crossed factor in cross-classified multilevel modeling. Front Psychol. 2021;12:637645. https://doi.org/10.3389/fpsyg.2021.637645
Portet S. A primer on model selection using the Akaike Information Criterion. Infect Dis Model. 2020;5:111-28. https://doi.org/10.1016/j.idm.2019.12.010
University of Bristol. Centre for Multilevel Modelling. 2022. MLwiN. Fecha de consulta: 28 de febrero de 2023. Disponible en: http://www.bristol.ac.uk/cmm/software/mlwin/
Albright JJ, Marinova DM. Estimating multilevel models using SPSS. Stata. 2010; Fecha de consulta: 28 de febrero de 2023. Disponible en: https://scholarworks.iu.edu/dspace/handle/2022/19737
Flores MW, Cook BL, Mullin B, Halperin-Goldstein G, Nathan A, Tenso K, et al. Associations between neighborhood-level factors and opioid-related mortality: A multilevel analysis using death certificate data. Addict Abingdon Engl. 2020;115:1878-89. https://doi.org/10.1111/add.15009
Shrout MR, Renna ME, Madison AA, Alfano CM, Povoski SP, Lipari AM, et al. Relationship satisfaction predicts lower stress and inflammation in breast cancer survivors: A longitudinal study of within-person and between-person effects. Psychoneuroendocrinology. 2020;118:104708. https://doi.org/10.1016/j.psyneuen.2020.104708
Park HC, Kim DK, Kho SY, Park PY. Cross-classified multilevel models for severity of commercial motor vehicle crashes considering heterogeneity among companies and regions. Accid Anal Prev. 2017;106:305-14. https://doi.org/10.1016/j.aap.2017.06.009
Evans CR, Williams DR, Onnela JP, Subramanian SV. A multilevel approach to modeling health inequalities at the intersection of multiple social identities. Soc Sci Med. 2018;203:64-73. https://doi.org/10.1016/j.socscimed.2017.11.011
Arias-Uriona AM, Losantos M, Bedoya P. La interseccionalidad como herramienta teóricoanalítica para estudiar las desigualdades en salud en las Américas. Rev Panam Salud Pública. 2023;47:1.
Some similar items:
- Luz Elena Velásquez, Catalina Gómez, Erika Valencia, Laura Salazar, Eudoro Casas, Paragonimosis in the peri-urban zone of Medellín, Antioquia , Biomedica: Vol. 28 No. 3 (2008)
- Juan Gabriel Piñeros, Malaria and social health determinants: a new heuristic framework from the perspective of Latin American social medicine , Biomedica: Vol. 30 No. 2 (2010)
- Sandra Milena Arias, Lina Marcela Salazar, Eudoro Casas, Alexandra Henao, Luz Elena Velásquez, Paragonimus sp. in crabs and awareness of the educational community to aquatic ecosystems in La Miel and La Clara, Caldas, Antioquia , Biomedica: Vol. 31 No. 2 (2011)
- Jaiberth Cardona-Arias, Luz Peláez-Vanegas, Juan López-Saldarriaga, Marcela Duque-Molina, Oscar Leal-Álvarez, Health related quality of life in adults with HIV/AIDS in Colombia , Biomedica: Vol. 31 No. 4 (2011)
- Laura A. Rodríguez-Villamizar, Beatriz Elena González, Lina María Vera, Jonathan Patz, Leonelo E. Bautista, Environmental and occupational health research and training needs in Colombia: A Delphi study , Biomedica: Vol. 35 (2015): Agosto, Suplemento 2, Salud y contaminantes ambientales
- Julián Alfredo Fernández-Niño, Rosa Ivonne Hernández-Montes, Laura Andrea Rodríguez-Villamizar, Reporting of statistical regression analyses in Biomédica: A critical assessment review , Biomedica: Vol. 38 No. 2 (2018)
- Ana Yibby Forero Torres, Luis Carlos Forero, Comparison between anthropometric measurements and indices to evaluate general and abdominal obesity, Colombia ENSIN 2015 , Biomedica: Vol. 43 No. Sp. 3 (2023): Enfermedades crónicas no transmisibles
Copyright (c) 2023 Biomedica
This work is licensed under a Creative Commons Attribution 4.0 International License.
| Article metrics | |
|---|---|
| Abstract views | |
| Galley vies | |
| PDF Views | |
| HTML views | |
| Other views | |
