Evidence map›Paper›PMID 30815417›Full record

ArticleMedical journal of the Islamic Republic of Iran2018

A brief guide to propensity score analysis.

Ameneh Ebrahim Valojerdi, Leila Janani

Abstract read
In one paragraph

Article in Medical journal of the Islamic Republic of Iran, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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  11. Bayesian methods for clinicians.Medical journal of the Islamic Republic of Iran · 2020
    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.

Ameneh Ebrahim ValojerdiEndocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences, Tehran, Iran.
Leila JananiDepartment of Biostatistics, School of Public Health, Iran University of Medical Sciences, Tehran, Iran, & Preventive Medicine and Public Health Research Center, Iran University of medical sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the statistical analysis of observational data, propensity score is a technique that attempts to estimate the effect of a treatment (exposure) by accounting for the covariates that predict receiving the treatment (exposure). The aim of this paper is to provide a brief guide for clinicians and researchers who are applying propensity score analysis as a tool for analyzing observational data. We reviewed literature about how, when and why propensity score is used and then we discussed some important practical issues in using propensity score in observational studies. Appling propensity score as a method for analyzing observational studies is very useful but, we should know when and how we can use this method. Moreover, new methods of propensity score analysis such as Bayesian and doubly robust approaches were established in recent years, and these methods could be more useful for researchers in estimating causal effect from observational studies.

Indexed as

Causal inferenceObservational studyPropensity score

Identifiers

PMID30815417
PMCPMC6387794

What OpenQuestion holds

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LicenceCC BY-NC
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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.