Random error units, extension of a novel method to express random error in epidemiological studies.

Imre Janszky, Johan Håkon Bjørngaard, Pål Romundstad, Lars Vatten, Nicola Orsini

Abstract read

In one paragraph

Article in Clinical epidemiology, 2019. 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

5 authors.

Imre JanszkyDeparment of Public Health, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway, imre.janszky@ntnu.no.

Johan Håkon BjørngaardDeparment of Public Health, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway, imre.janszky@ntnu.no.

Pål RomundstadDeparment of Public Health, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway, imre.janszky@ntnu.no.

Lars VattenDeparment of Public Health, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway, imre.janszky@ntnu.no.

Nicola OrsiniDepartment of Public Health Sciences, Karolinska Insitutet, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently used methods to express random error are often misinterpreted and consequently misused by biomedical researchers. Previously we proposed a simple approach to quantify the amount of random error in epidemiological studies using OR for binary exposures. Expressing random error with the number of random error units (REU) does not require solid background in statistics for a proper interpretation and cannot be misused for making oversimplistic interpretations relying on statistical significance. We now expand the use of REU to the most common measures of associations in epidemiology and to continuous variables, and we have developed a Stata program, which greatly facilitates the calculation of REU.

Indexed as

confidence intervalsP Valuerandom errorrandom error unitsstatistical significance

Identifiers

PMID30774447

DOI10.2147/CLEP.S184231

PMCPMC6350827

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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.