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Pregled bibliografske jedinice broj: 420725

The most common statistical mistakes in biomedical literature


Šimundić, Ana-Maria
The most common statistical mistakes in biomedical literature // Abstracts of the 18th IFCC - EFCC European Congress of Clinical Chemistry and Laboratory Medicine (Euromedlab 2009) ; u: Clinical Chemistry and Laboratory Medicine 47 (2009) (S) ; S1 – S409 / Siest, Gerhard (ur.).
Innsbruck: Walter de Gruyter, 2009. str. 61-61 (pozvano predavanje, nije recenziran, sažetak, znanstveni)


CROSBI ID: 420725 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
The most common statistical mistakes in biomedical literature

Autori
Šimundić, Ana-Maria

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Abstracts of the 18th IFCC - EFCC European Congress of Clinical Chemistry and Laboratory Medicine (Euromedlab 2009) ; u: Clinical Chemistry and Laboratory Medicine 47 (2009) (S) ; S1 – S409 / Siest, Gerhard - Innsbruck : Walter de Gruyter, 2009, 61-61

Skup
IFCC - EFCC European Congress of Clinical Chemistry and Laboratory Medicine (18 ; 2009)

Mjesto i datum
Innsbruck, Austrija, 07.06.2009. - 11.06.2009

Vrsta sudjelovanja
Pozvano predavanje

Vrsta recenzije
Nije recenziran

Ključne riječi
errors; biostatistics; methodology
(pogrješke; biostatistika; metodologija)

Sažetak
Most scientific journals have a statistical editor whose task is to assure that authors of the papers published, report their results in a proper way. Furthermore, many journals have published guidelines concerning research methodology, study design, data analysis and reporting. Instructions on the use of statistical methodology are also usually included in the journal Instructions to authors and authors are oblidged to follow them. However, many papers published in the biomedical literature still have some major problems with research methodology and statistical analysis. This fact is well known and extensively discussed in the literature. Incorrect design of the study and statistical flaws inevitably lead to incorrect conclusions and such shortcommings may be misleading to the clinical practice and waste of the valuable health resources. Sampling error is one of the most often mistakes occuring in the biomedical literature. Sampling is a crucial to the validity of the study. If study groups are not representative for the population, authors are not allowed to use inferential statistical techniques, i.e. to make conclusions about the population. Sample size should be appropriate in order to avoid mistakes in statistical hypothesis testing. Choice of the proper statistical test is also a common statistical mistake. Authors are often unaware of the assumptions that need to be met when applying some statistical test for data analysis. These assumptions are concerning the data distribution characteristics, scale of measurement, sample size, number of groups and observations and some other. Another common mistake is the erroneous data presentation such as the incorrect use of summary measures, data reported with an inconceivable precision and missleading graphical presentations. P value is commonly incorrectly reported and its meaning often misinterpreted. Furthermore, authors often make incorrect conclusions based solely on the P value, disregarding the clinical significance of the results. Results obtained should be always interpreted relevant to their clinical significance. One of the most important shortcommings of the manuscripts submitted to biomedical journals are incorrect conclusions. Drawing conclusions should be solely based on the obtained results. This fact is very often overseen by authors. A commonly occuring mistake is conclusion on the causality of the observed relationship when there is actually no causal relationship. It is a frequent missinterpretation of the correlation analysis. Last, but not the least, the issue of multiple hypothesis testing is widely present in the published biomedical reports. Both, authors and editors should be aware of the importance of uses and misusses of statistical analysis. Each step forward in educating potential future authors is beneficial to the level of the ethical, professional and competent research practice as well as to the quality of the papers to be submitted.

Izvorni jezik
Engleski

Znanstvena područja
Kliničke medicinske znanosti



POVEZANOST RADA


Projekti:
134-1340227-0200 - Upala i udio farmakogenetike u razvoju i ishodu akutnih i kroničnih bolesti (Šimundić, Ana-Maria, MZOS ) ( CroRIS)

Ustanove:
KBC "Sestre Milosrdnice"

Profili:

Avatar Url Ana-Maria Šimundić (autor)


Citiraj ovu publikaciju:

Šimundić, Ana-Maria
The most common statistical mistakes in biomedical literature // Abstracts of the 18th IFCC - EFCC European Congress of Clinical Chemistry and Laboratory Medicine (Euromedlab 2009) ; u: Clinical Chemistry and Laboratory Medicine 47 (2009) (S) ; S1 – S409 / Siest, Gerhard (ur.).
Innsbruck: Walter de Gruyter, 2009. str. 61-61 (pozvano predavanje, nije recenziran, sažetak, znanstveni)
Šimundić, A. (2009) The most common statistical mistakes in biomedical literature. U: Siest, G. (ur.)Abstracts of the 18th IFCC - EFCC European Congress of Clinical Chemistry and Laboratory Medicine (Euromedlab 2009) ; u: Clinical Chemistry and Laboratory Medicine 47 (2009) (S) ; S1 – S409.
@article{article, author = {\v{S}imundi\'{c}, Ana-Maria}, editor = {Siest, G.}, year = {2009}, pages = {61-61}, keywords = {errors, biostatistics, methodology}, title = {The most common statistical mistakes in biomedical literature}, keyword = {errors, biostatistics, methodology}, publisher = {Walter de Gruyter}, publisherplace = {Innsbruck, Austrija} }
@article{article, author = {\v{S}imundi\'{c}, Ana-Maria}, editor = {Siest, G.}, year = {2009}, pages = {61-61}, keywords = {pogrje\v{s}ke, biostatistika, metodologija}, title = {The most common statistical mistakes in biomedical literature}, keyword = {pogrje\v{s}ke, biostatistika, metodologija}, publisher = {Walter de Gruyter}, publisherplace = {Innsbruck, Austrija} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE





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