Evidence map›Paper›PMID 31263291›Full record

ArticleThe American statistician2019

Limitations of P-Values and R-squared for Stepwise Regression Building: A Fairness Demonstration in Health Policy Risk Adjustment.

Sherri Rose, Thomas G McGuire

Abstract read
In one paragraph

Article in The American statistician, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  9. Use of past care markers in risk-adjustment: accounting for systematic differences across providers.The European journal of health economics : HEPAC : health economics in prevention and care · 2022
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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

2 authors.

Sherri RoseDepartment of Health Care Policy, Harvard Medical School, Boston, MA, 01201 (rose@hcp.med.harvard.edu).
Thomas G McGuireDepartment of Health Care Policy, Harvard Medical School, Boston, MA 01201 and Research Associate at NBER, Cambridge, MA, 02138.

Funding

Machine Learning for Health Outcomes and Quality of Care in Low-Income PopulationsDP2MD012722 · NIMHD · STANFORD UNIVERSITY · PI ROSE, SHERRI · 2017 to 2017
$2.5M
NIMHD NIH HHS DP2 MD012722
6 · The paper itself

Abstract

Stepwise regression building procedures are commonly used applied statistical tools, despite their well-known drawbacks. While many of their limitations have been widely discussed in the literature, other aspects of the use of individual statistical fit measures, especially in high-dimensional stepwise regression settings, have not. Giving primacy to individual fit, as is done with p-values and R

Indexed as

fairnesshealth policyp-valuerisk adjustmentstepwise regression

Identifiers

PMID31263291
PMCPMC6602076

What OpenQuestion holds

Textmetadata
LicenceTDM
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.