Evidence map›Paper›PMID 28629262›Full record

ArticleHealth psychology review2017

Dynamic modelling of n-of-1 data: powerful and flexible data analytics applied to individualised studies.

Rute Vieira, Suzanne McDonald, Vera Araújo-Soares, Falko F Sniehotta, Robin Henderson

Abstract read
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In one paragraph

Article in Health psychology review, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 2 pooled it
–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

41 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Rute Vieiraa Institute of Health & Society, Newcastle University , Newcastle upon Tyne , UK.
Suzanne McDonalda Institute of Health & Society, Newcastle University , Newcastle upon Tyne , UK.
Vera Araújo-Soaresa Institute of Health & Society, Newcastle University , Newcastle upon Tyne , UK.
Falko F Sniehottab Fuse, UKCRC Centre for Translational Research in Public Health, Institute of Health & Society, Newcastle University , Newcastle upon Tyne , UK.
Robin Hendersonc School of Mathematics and Statistics, Newcastle University , Newcastle upon Tyne , UK.

Funding

British Heart FoundationCancer Research UKMedical Research Council MR/K02325X/1
6 · The paper itself

Abstract

N-of-1 studies are based on repeated observations within an individual or unit over time and are acknowledged as an important research method for generating scientific evidence about the health or behaviour of an individual. Statistical analyses of n-of-1 data require accurate modelling of the outcome while accounting for its distribution, time-related trend and error structures (e.g., autocorrelation) as well as reporting readily usable contextualised effect sizes for decision-making. A number of statistical approaches have been documented but no consensus exists on which method is most appropriate for which type of n-of-1 design. We discuss the statistical considerations for analysing n-of-1 studies and briefly review some currently used methodologies. We describe dynamic regression modelling as a flexible and powerful approach, adaptable to different types of outcomes and capable of dealing with the different challenges inherent to n-of-1 statistical modelling. Dynamic modelling borrows ideas from longitudinal and event history methodologies which explicitly incorporate the role of time and the influence of past on future. We also present an illustrative example of the use of dynamic regression on monitoring physical activity during the retirement transition. Dynamic modelling has the potential to expand researchers' access to robust and user-friendly statistical methods for individualised studies.

Indexed as

Decision MakingModels, StatisticalHumansObservational Studies as TopicResearch Designdynamic regressionindividualised studyN-of-1 methodssingle-case

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.