Evidence map›Paper›PMID 31501916›Full record

ReviewHNO2020

[Pitfalls in the statistical world].

C Kiese-Himmel, S K Plontke

Abstract readReview
PubMed Publisher
In one paragraph

Review in HNO, 2020. 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

2 authors.

C Kiese-HimmelPhoniatrisch/Pädaudiologische Psychologie, Universitätsmedizin Göttingen, Waldweg 35, 37073, Göttingen, Deutschland. ckiese@med.uni-goettingen.de.
S K PlontkeUniversitätsklinik und Poliklinik für Hals-Nasen-Ohren-Heilkunde, Kopf- und Hals-Chirurgie, Martin-Luther-Universität Halle-Wittenberg, Halle (Saale), Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mistakes in the acquisition, evaluation, analysis and reporting of data often occur because there is a lack of awareness of the methodological problem. They can have far-reaching consequences for the reception of results of scientific primary studies and therefore for the clinical practice and healthcare. This article aims at raising awareness for a responsible handling of study data and for avoiding questionable or incorrect practices. It presents some examples of statistical pitfalls in empirical research practice, which increase the probability of false positive results and shows possibilities to avoid such risks.

Indexed as

Data Interpretation, StatisticalFalse positive findingsHARKingp-hackingPreregistrationReplicability

Identifiers

What OpenQuestion holds

Textmetadata
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.