Evidence map›Paper›PMID 38598916›Full record

ArticleJournal of health economics2024

Analyzing health outcomes measured as bounded counts.

John Mullahy

Abstract read
In one paragraph

Article in Journal of health economics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

John MullahyUniversity of Wisconsin-Madison, Madison, WI, USA; Univiversity of Galway, Galway, Ireland; NBER, Cambridge, MA, USA. Electronic address: jmullahy@wisc.edu.

Funding

Statistical Data Enclave CoreP30AG017266 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Michal Engelman · 1999 to 2026
$17.0M
Center for Demography and EcologyR24HD047873 · NICHD · UNIVERSITY OF WISCONSIN-MADISON · PI RAYMO, JAMES M · 2004 to 2013
$7.2M
Scientific and Technical CoreP2CHD047873 · NICHD · UNIVERSITY OF WISCONSIN-MADISON · PI Katherine J. Curtis · 2014 to 2026
$5.1M
NIA NIH HHS P30 AG017266NICHD NIH HHS P2C HD047873NICHD NIH HHS R24 HD047873
6 · The paper itself

Abstract

This paper assesses analytical strategies that respect the bounded-count nature of health outcomes encountered often in empirical applications. Absent in the literature is a comprehensive discussion and critique of strategies for analyzing and understanding such data. The paper's goal is to provide an in-depth consideration of prominent issues arising in and strategies for undertaking such analyses, emphasizing the merits and limitations of various analytical tools empirical researchers may contemplate. Three main topics are covered. First, bounded-count health outcomes' measurement properties are reviewed and their implications assessed. Second, issues arising when bounded-count outcomes are the objects of concern in evaluations are described. Third, the (conditional) probability and moment structures of bounded-count outcomes are derived and corresponding specification and estimation strategies presented with particular attention to partial effects. Many questions may be asked of such data in health research and a researcher's choice of analytical method is often consequential.

Indexed as

Outcome Assessment, Health CareData Interpretation, StatisticalHumansModels, StatisticalProbabilityBounded outcomesCount data

Identifiers

PMID38598916
PMCPMC11102836

What OpenQuestion holds

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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.