Evidence map›Paper›PMID 24350198›Full record

ArticleFrontiers in public health2013

Assessing the Relationship between the Baseline Value of a Continuous Variable and Subsequent Change Over Time.

Arnaud Chiolero, Gilles Paradis, Benjamin Rich, James A Hanley

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In one paragraph

Article in Frontiers in public health, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Trial
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  17. Future Thinking Priming Especially Effective at Modifying Delay Discounting Rates among Cigarette Smokers.International journal of environmental research and public health · 2021
    Article
  18. Short Leukocyte Telomeres, But Not Telomere Attrition Rates, Predict Memory Decline in the 20-Year Longitudinal Betula Study.The journals of gerontology. Series A, Biological sciences and medical sciences · 2021
    Article
  19. Article
  20. 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

4 authors.

Arnaud ChioleroUniversity Hospital Center, Institute of Social and Preventive Medicine (IUMSP), University of Lausanne , Lausanne , Switzerland ; Department of Epidemiology, Biostatistics, and Occupational Health, McGill University , Montreal, QC , Canada.
Gilles ParadisDepartment of Epidemiology, Biostatistics, and Occupational Health, McGill University , Montreal, QC , Canada ; McGill University Health Center Research Institute , Montreal, QC , Canada ; Public Health Institute of Quebec , Montreal, QC , Canada.
Benjamin RichDepartment of Epidemiology, Biostatistics, and Occupational Health, McGill University , Montreal, QC , Canada.
James A HanleyDepartment of Epidemiology, Biostatistics, and Occupational Health, McGill University , Montreal, QC , Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analyzing the relationship between the baseline value and subsequent change of a continuous variable is a frequent matter of inquiry in cohort studies. These analyses are surprisingly complex, particularly if only two waves of data are available. It is unclear for non-biostatisticians where the complexity of this analysis lies and which statistical method is adequate. With the help of simulated longitudinal data of body mass index in children, we review statistical methods for the analysis of the association between the baseline value and subsequent change, assuming linear growth with time. Key issues in such analyses are mathematical coupling, measurement error, variability of change between individuals, and regression to the mean. Ideally, it is better to rely on multiple repeated measurements at different times and a linear random effects model is a standard approach if more than two waves of data are available. If only two waves of data are available, our simulations show that Blomqvist's method - which consists in adjusting for measurement error variance the estimated regression coefficient of observed change on baseline value - provides accurate estimates. The adequacy of the methods to assess the relationship between the baseline value and subsequent change depends on the number of data waves, the availability of information on measurement error, and the variability of change between individuals.

Indexed as

baseline valuechangemathematical couplingmeasurement errorregression to the mean

Identifiers

PMID24350198
PMCPMC3854983

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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.