A log-Weibull spatial scan statistic for time to event data.

Abstract read

In one paragraph

Article in International journal of health geographics, 2018. 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.

A Shared-Frailty Spatial Scan Statistic Model for Time-to-Event Data.Biometrical journal. Biometrische Zeitschrift · 2024
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

2 authors.

Iram UsmanDepartment of Pediatrics, 3-077, Edmonton Clinic Health Academy, University of Alberta, 11405 87 Avenue NW, Edmonton, AB, T6G 1C9, Canada.

Rhonda J RosychukDepartment of Pediatrics, 3-524, Edmonton Clinic Health Academy, University of Alberta, 11405 87 Avenue NW, Edmonton, AB, T6G 1C9, Canada. rhonda.rosychuk@ualberta.ca.ORCID 0000-0001-8019-5466

Funding

Natural Sciences and Engineering Research Council of Canada Discovery Grant

6 · The paper itself

Abstract

backgroundSpatial scan statistics have been used for the identification of geographic clusters of elevated numbers of cases of a condition such as disease outbreaks. These statistics accompanied by the appropriate distribution can also identify geographic areas with either longer or shorter time to events. Other authors have proposed the spatial scan statistics based on the exponential and Weibull distributions.

resultsWe propose the log-Weibull as an alternative distribution for the spatial scan statistic for time to events data and compare and contrast the log-Weibull and Weibull distributions through simulation studies. The effect of type I differential censoring and power have been investigated through simulated data. Methods are also illustrated on time to specialist visit data for discharged patients presenting to emergency departments for atrial fibrillation and flutter in Alberta during 2010-2011. We found northern regions of Alberta had longer times to specialist visit than other areas.

conclusionsWe proposed the spatial scan statistic for the log-Weibull distribution as a new approach for detecting spatial clusters for time to event data. The simulation studies suggest that the test performs well for log-Weibull data.

Indexed as

Data AnalysisGeographic MappingModels, StatisticalAlbertaAtrial FibrillationComputer SimulationEmergency Service, HospitalHumansMonte Carlo MethodTime FactorsAtrial fibrillation and flutterEmergency departmentLog-Weibull distributionSpatial scan statisticTime to event

Identifiers

PMID29895308

DOI10.1186/s12942-018-0137-9

PMCPMC5998574

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LicenceCC BY

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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.