TY - JOUR
T1 - Common errors of interpretation in biostatistics
AU - Arreola, Elsa Vazquez
AU - Irimata, Kyle
AU - Wilson, Jeffrey R.
N1 - Publisher Copyright:
© 2020, © 2020 International Biometric Society–Chinese Region.
PY - 2020
Y1 - 2020
N2 - What do we wish to investigate? While this may be a common question in research, it does not always come with straightforward answers. This article reviews data-driven methods of collection, questions asked and questions answered, and the myriad of different conclusions that may result. We examine differences in answers to questions based on independent versus correlated observations, bivariate versus conditional associations, relations versus extrapolation, and single membership versus multiple membership modeling. Regardless of the issue, these differences are usually not due to so-called bad data or due to bad models; they are usually due to the investigators misinterpreting the answers that were given. Most importantly, one cannot ask a question and obtain an answer without understanding the data structure, its size and its representativeness. Simply stated, the fact that I went to the store and bought an outfit does not mean the outfit is appropriate for the event. The answers obtained may not be answering the question of interest.
AB - What do we wish to investigate? While this may be a common question in research, it does not always come with straightforward answers. This article reviews data-driven methods of collection, questions asked and questions answered, and the myriad of different conclusions that may result. We examine differences in answers to questions based on independent versus correlated observations, bivariate versus conditional associations, relations versus extrapolation, and single membership versus multiple membership modeling. Regardless of the issue, these differences are usually not due to so-called bad data or due to bad models; they are usually due to the investigators misinterpreting the answers that were given. Most importantly, one cannot ask a question and obtain an answer without understanding the data structure, its size and its representativeness. Simply stated, the fact that I went to the store and bought an outfit does not mean the outfit is appropriate for the event. The answers obtained may not be answering the question of interest.
KW - Correlated data
KW - hierarchical level data
KW - hypotheses
KW - logistic regression
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U2 - 10.1080/24709360.2020.1790085
DO - 10.1080/24709360.2020.1790085
M3 - Article
AN - SCOPUS:85088146981
SN - 2470-9360
SP - 238
EP - 246
JO - Biostatistics and Epidemiology
JF - Biostatistics and Epidemiology
ER -