Evidence map›Paper›PMID 36750263›Full record

ReviewAnnual review of clinical psychology2023

The Questionable Practice of Partialing to Refine Scores on and Inferences About Measures of Psychological Constructs.

Rick H Hoyle, Donald R Lynam, Joshua D Miller, Jolynn Pek

Abstract readReview
In one paragraph

Review in Annual review of clinical psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. The social ambivalence and disease model: Childhood trauma as an antecedent factor linking spousal ambivalence to inflammation.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2026
    Article
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  12. Antisocial personality traits as potential risk factors for cyberstalking: only aspects of psychopathy and narcissism matter.Psychiatry, psychology, and law : an interdisciplinary journal of the Australian and New Zealand Association of Psychiatry, Psychology and Law · 2025
    Article
  13. Causal inference on human behaviour.Nature human behaviour · 2024
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
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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.

Rick H HoyleDepartment of Psychology and Neuroscience, Duke University, Durham, North Carolina, USA; email: rhoyle@duke.edu.
Donald R LynamDepartment of Psychological Sciences, Purdue University, West Lafayette, Indiana, USA.
Joshua D MillerDepartment of Psychology, University of Georgia, Athens, Georgia, USA.
Jolynn PekDepartment of Psychology, Ohio State University, Columbus, Ohio, USA.

Funding

TRANSLATION AND DISSEMINATION COREP30DA023026 · NIDA · DUKE UNIVERSITY · PI HOYLE, RICK · 2008 to 2023
$19.6M
NIDA NIH HHS P30 DA023026
6 · The paper itself

Abstract

Partialing is a statistical approach researchers use with the goal of removing extraneous variance from a variable before examining its association with other variables. Controlling for confounds through analysis of covariance or multiple regression analysis and residualizing variables for use in subsequent analyses are common approaches to partialing in clinical research. Despite its intuitive appeal, partialing is fraught with undesirable consequences when predictors are correlated. After describing effects of partialing on variables, we review analytic approaches commonly used in clinical research to make inferences about the nature and effects of partialed variables. We then use two simulations to show how partialing can distort variables and their relations with other variables. Having concluded that, with rare exception, partialing is ill-advised, we offer recommendations for reducing or eliminating problematic uses of partialing. We conclude that the best alternative to partialing is to define and measure constructs so that it is not needed.

Indexed as

construct validityquestionable measurement practiceresidualized variablessemipartial effectsstatistical control

Identifiers

PMID36750263
PMCPMC11331532

What OpenQuestion holds

Textmetadata
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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.