Evidence map›Paper›PMID 36076295›Full record

Trial reportTrials2022

Performance of model-based vs. permutation tests in the HEALing (Helping to End Addiction Long-term

Xiaoyu Tang, Timothy Heeren, Philip M Westgate, Daniel J Feaster, Soledad A Fernandez, Nathan Vandergrift, Debbie M Cheng

Registry-linked trialAbstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Trials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04111939 (HEALing Communities Study), which is not on this 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.

NCT04111939 nacompletednot on this map

HEALing Communities Study: Developing and Testing an Integrated Approach to Address the Opioid Crisis

TypeinterventionalSponsorRTI InternationalRan2019 to 2025Enrolled67ConditionsOpioid Use Disorder (OUD)ArmsCommunities That HEAL, Wait-list control
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.

Xiaoyu TangDepartment of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA, 02219, USA. rainie@bu.edu.ORCID http://orcid.org/0000-0002-7236-3201
Timothy HeerenDepartment of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA, 02219, USA.
Philip M WestgateDepartment of Biostatistics, University of Kentucky College of Public Health, Lexington, USA.
Daniel J FeasterDepartment of Public Health Sciences, University of Miami, Coral Gables, FL, USA.
Soledad A FernandezDepartment of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, USA.
Nathan VandergriftRTI International, Research Triangle, NC, USA.
Debbie M ChengDepartment of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA, 02219, USA.

Funding

NIDA NIH HHS UM1 DA049406
6 · The paper itself

Abstract

backgroundThe HEALing (Helping to End Addiction Long-term

methodsThe primary outcome, the number of opioid overdose deaths, is count data assessed at the community level that will be analyzed using a negative binomial regression model. We conducted a simulation study to evaluate the type I error rates and power for 3 tests: (1) Wald-type t-test with small-sample corrected empirical standard error estimates, (2) Wald-type z-test with model-based standard error estimates, and (3) permutation test with test statistics calculated by the difference in average residuals for the two groups.

resultsOur simulation results demonstrated that Wald-type t-tests with small-sample corrected empirical standard error estimates from the negative binomial regression model maintained proper type I error. Wald-type z-tests with model-based standard error estimates were anti-conservative. Permutation tests preserved type I error rates if the constrained space was not too small. For all tests, the power was high to detect the hypothesized 40% reduction in opioid overdose deaths for the intervention vs. comparison group both for the overall HCS and the subgroup analysis of Massachusetts (MA).

conclusionsBased on the results of our simulation study, the Wald-type t-test with small-sample corrected empirical standard error estimates from a negative binomial regression model is a valid and appropriate approach for analyzing cluster-level count data from the HEALing Communities Study.

trial registrationClinicalTrials.gov http://www. CLINICALTRIALS: gov ; Identifier: NCT04111939.

Indexed as

Opiate OverdoseComputer SimulationHumansMassachusettsModels, StatisticalRandom AllocationCluster randomized trialsCovariate-constrained randomizationModel-based testsNegative binomial regressionPermutation tests

Identifiers

PMID36076295
PMCPMC9461200

What Socratic holds

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Registered trials

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 Socratic graph.