Evidence map›Paper›PMID 38323522›Full record

ArticleAssessment2024

The Effect of Missing Item Data on the Relative Predictive Accuracy of Correctional Risk Assessment Tools.

Bronwen Perley-Robertson, Kelly M Babchishin, L Maaike Helmus

Abstract read
In one paragraph

Article in Assessment, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Bronwen Perley-RobertsonCarleton University, Ottawa, Ontario, Canada.ORCID 0000-0002-5786-0816
Kelly M BabchishinCarleton University, Ottawa, Ontario, Canada.
L Maaike HelmusSimon Fraser University, Burnaby, British Columbia, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Missing data are pervasive in risk assessment but their impact on predictive accuracy has largely been unexplored. Common techniques for handling missing risk data include summing available items or proration; however, multiple imputation is a more defensible approach that has not been methodically tested against these simpler techniques. We compared the validity of these three missing data techniques across six conditions using STABLE-2007 (

Indexed as

PrisonersAdultCanadaHumansMaleMiddle AgedReproducibility of ResultsRisk Assessmentcorrectional risk assessmentdomestic violence recidivismmissing datapredictive accuracysexual recidivism

Identifiers

PMID38323522
PMCPMC11490059

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.