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Scientific rigour in psycho‐oncology trials: why and how to avoid common statistical errors
Author(s) -
Bell Melanie L.,
Olivier Jake,
King Madeleine T.
Publication year - 2013
Publication title -
psycho‐oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.41
H-Index - 137
eISSN - 1099-1611
pISSN - 1057-9249
DOI - 10.1002/pon.3046
Subject(s) - rigour , psychology , categorization , commit , field (mathematics) , medical education , data science , computer science , medicine , epistemology , mathematics , philosophy , database , artificial intelligence , pure mathematics
Objective It is well documented that statistical and methodological flaws are common in much of the health research literature, including psycho‐oncology. These can have far‐reaching effects, including the publishing of misleading results; the wasting of time, effort, and financial resources; exposure of patients to the potential harms of research and decreased confidence in science and researchers by the public. Methods Several of the most common statistical errors and methodological pitfalls that occur in the field of psycho‐oncology are discussed, including those that occur at the design, analysis, reporting and conclusion stages. Results Fourteen topics are briefly discussed, explaining why there is a problem and how to avoid it. These include proper approaches to power, clustering, missing data, categorization of continuous variables, subgroup analyses, multiple comparisons, statistical interactions, confidence intervals and correct interpretation of p ‐values. Extensive referencing points the reader to more in‐depth explanations. Conclusions To increase the scientific rigour in psycho‐oncology, researchers should involve a biostatistician from the beginning of the study and should commit to continuing education on best practices in the fields of statistics and reporting. Copyright © 2012 John Wiley & Sons, Ltd.