Evidence map›Paper›PMID 27537692›Full record

ArticlePloS one2016

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

Eric Houngla Adjakossa, Ibrahim Sadissou, Mahouton Norbert Hounkonnou, Gregory Nuel

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

4 authors.

Eric Houngla AdjakossaLaboratoire de Probabilités et Modèles Aléatoires /Université Pierre et Marie Curie, Case courrier 188 - 4, Place Jussieu 75252 Paris cedex 05 France.
Ibrahim SadissouLaboratoire de Biologie et de Physiologie Cellulaires /University of Abomey-Calavi, Cotonou, Republic of Benin.
Mahouton Norbert HounkonnouUniversity of Abomey-Calavi, 072 B.P. 50 Cotonou, Republic of Benin.
Gregory NuelLaboratoire de Probabilités et Modèles Aléatoires /Université Pierre et Marie Curie, Case courrier 188 - 4, Place Jussieu 75252 Paris cedex 05 France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

Indexed as

Longitudinal StudiesModels, StatisticalMultivariate AnalysisAlgorithmsData Interpretation, StatisticalHumansLinear Models

Identifiers

PMID27537692
PMCPMC4990185

What OpenQuestion holds

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Registered trials

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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.