Evidence map›Paper›PMID 28352203›Full record

ArticleClinical epidemiology2017

Missing data and multiple imputation in clinical epidemiological research.

Alma B Pedersen, Ellen M Mikkelsen, Deirdre Cronin-Fenton, Nickolaj R Kristensen, Tra My Pham, Lars Pedersen, Irene Petersen

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05173532 (The Prescriptive Validity of a Novel Fall Risk Clinical Prediction Rule for People With COPD), which is not on this map. Cited by 415 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
415citing papers in PubMed, 3 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.

NCT05173532 naunknown statusnot on this mapstarted 2021, after this paper: background citation

The Prescriptive Validity of a Novel Fall Risk Clinical Prediction Rule for People With COPD

TypeinterventionalSponsorTexas Woman's UniversityRan2021 to 2022Enrolled88ConditionsPulmonary Disease, Chronic ObstructiveArmsBalance Training, Breathing and Stretching Exercises
3 · Its place in the literature

Who cites it

415 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  7. Influence of Social Support on Patients' Adherence to Activity Advice in Low Back Pain: A Double-Blinded Randomised Controlled Trial.Physiotherapy research international : the journal for researchers and clinicians in physical therapy · 2026
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  11. Prevalence and risk factors of maternal dissatisfaction after vaginal delivery: A multicenter prospective study.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025
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355 more citing papers are in PubMed but not listed here.

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

7 authors.

Alma B PedersenDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus N, Denmark.
Ellen M MikkelsenDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus N, Denmark.
Deirdre Cronin-FentonDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus N, Denmark.
Nickolaj R KristensenDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus N, Denmark.
Tra My PhamDepartment of Primary Care and Population Health, University College London, London, UK.
Lars PedersenDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus N, Denmark.
Irene PetersenDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus N, Denmark; Department of Primary Care and Population Health, University College London, London, UK.

Funding

Medical Research Council G0900701
6 · The paper itself

Abstract

Missing data are ubiquitous in clinical epidemiological research. Individuals with missing data may differ from those with no missing data in terms of the outcome of interest and prognosis in general. Missing data are often categorized into the following three types: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). In clinical epidemiological research, missing data are seldom MCAR. Missing data can constitute considerable challenges in the analyses and interpretation of results and can potentially weaken the validity of results and conclusions. A number of methods have been developed for dealing with missing data. These include complete-case analyses, missing indicator method, single value imputation, and sensitivity analyses incorporating worst-case and best-case scenarios. If applied under the MCAR assumption, some of these methods can provide unbiased but often less precise estimates. Multiple imputation is an alternative method to deal with missing data, which accounts for the uncertainty associated with missing data. Multiple imputation is implemented in most statistical software under the MAR assumption and provides unbiased and valid estimates of associations based on information from the available data. The method affects not only the coefficient estimates for variables with missing data but also the estimates for other variables with no missing data.

Indexed as

MARMCARmissing dataMNARmultiple imputationobservational study

Identifiers

PMID28352203
PMCPMC5358992

What OpenQuestion holds

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Registered trials

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.