When “facts” are not facts: what does p value really mean, and how does it deceive us?

The recent paper in JAMA alleging that frozen embryo transfer causes twice the risk of childhood cancer in the offspring is an excellent example of the erroneous use of statistical tests (and the misinterpretation of p value) that is common in much of the medical literature, even in very high impact...

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Bibliographic Details
Published in:Journal of assisted reproduction and genetics 2020-06, Vol.37 (6), p.1303-1310
Main Authors: Liao, Caiyun, Speirs, Andrew L., Goldsmith, Sierra, Silber, Sherman J.
Format: Article
Language:English
Subjects:
Child
Children
Commentary
Data Interpretation, Statistical
Embryo transfer
Embryo Transfer - adverse effects
Embryo Transfer - statistics & numerical data
Female
Gynecology
Human Genetics
Humans
Medicine
Medicine & Public Health
Neoplasms - epidemiology
Neoplasms - etiology
Reproductive Medicine
Risk Factors
Statistical analysis
Statistical significance
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Description
Summary:The recent paper in JAMA alleging that frozen embryo transfer causes twice the risk of childhood cancer in the offspring is an excellent example of the erroneous use of statistical tests (and the misinterpretation of p value) that is common in much of the medical literature, even in very high impact journals. These myths backed by misleading statements of “statistical significance” can cause far-reaching harm to patients and doctors who might not understand the pitfalls of specious statistical testing.
ISSN:1058-0468
1573-7330
DOI:10.1007/s10815-020-01751-4