Evidence map›Paper›PMID 38109143›Full record

ArticleBiomedica : revista del Instituto Nacional de Salud2023

Construction of multilevel statistical models in health research: Foundations and generalities

Andry Yasmid Mera-Mamián, José Moreno-Montoya, Laura Andrea Rodríguez-Villamizar, Diana Isabel Muñoz, Ángela María Segura, Héctor Iván García

Abstract readEnglish Abstract
In one paragraph

Article in Biomedica : revista del Instituto Nacional de Salud, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Andry Yasmid Mera-MamiánEscuela de Graduados, Universidad CES, Medellín, Colombia. mera.andry@uces.edu.co.ORCID 0000-0002-2356-3370
José Moreno-MontoyaDivisión de Estudios Clínicos y Epidemiología Clínica, Hospital Universitario de la Fundación Santa Fe de Bogotá, Bogotá, D.C., Colombia. josemorenomontoya@gmail.com.ORCID 0000-0001-8446-1231
Laura Andrea Rodríguez-VillamizarDepartamento de Salud Pública, Escuela de Medicina, Universidad Industrial de Santander, Bucaramanga, Colombia. laurovi@uis.edu.co.ORCID 0000-0002-5551-2586
Diana Isabel MuñozFacultad de Fisioterapia, Universidad CES, Medellín, Colombia. dmunoz@ces.edu.co.ORCID 0000-0003-4255-4813
Ángela María SeguraEscuela de Graduados, Universidad CES, Medellín, Colombia. asegura@ces.edu.co.ORCID 0000-0002-0010-1413
Héctor Iván GarcíaInstituto de Cancerología Las Américas, Medellín, Colombia. hgarcia@une.net.co.ORCID 0000-0002-3549-1263

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

biasbiostatisticshealth services researchMultilevel analysis

Identifiers

PMID38109143
PMCPMC10826466

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.