Evidence map›Paper›PMID 41804326›Full record

ArticleHealth services & outcomes research methodology2026

Choosing an analytic approach: key study design considerations in state policy evaluation.

Elizabeth M Stone, Megan S Schuler, Elizabeth A Stuart, Max Rubinstein, Max Griswold, Bradley D Stein, Beth Ann Griffin

Abstract read
In one paragraph

Article in Health services & outcomes research methodology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Elizabeth M StoneRutgers Institute for Health, Health Care Policy and Aging Research, 112 Paterson Street, Room 305, New Brunswick, NJ 08901 USA.
Megan S SchulerRAND Corporation, Washington, DC, USA.
Elizabeth A StuartDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA.
Max RubinsteinRAND Corporation, Pittsburgh, PA USA.
Max GriswoldRAND Corporation, Santa Monica, CA USA.
Bradley D SteinRAND Corporation, Pittsburgh, PA USA.
Beth Ann GriffinRAND Corporation, Santa Monica, CA USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper reviews and details methods for state policy evaluation to guide selection of a research approach, based on an evaluation's setting and available data. We highlight key design considerations for an analysis, including treatment and control group selection, timing of policy adoption, expected effect heterogeneity, and data considerations. We then provide an overview of analytic approaches and differentiate between methods based on an evaluation's context, such as settings with no control units, a single treated unit, multiple treated units, or with multiple treatment cohorts. Methods discussed include: interrupted time series models, difference-in-differences estimators, autoregressive models, and synthetic control methods, along with method extensions which address issues like staggered policy adoption and heterogenous treatment effects. We end with an illustrative example, applying the developed framework to evaluate the impacts of state-level naloxone standing order policies on overdose rates. Overall, we provide researchers with an approach for deciding on methods for state policy evaluations, which can be used to select study designs and inform methodological choices. Supplementary Information: The online version contains supplementary material available at 10.1007/s10742-025-00369-2.

Indexed as

Causal inferencePanel dataPolicy evaluationStatistical methodology

Identifiers

PMID41804326
PMCPMC12967469

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.