TY - JOUR
T1 - Seven items were identified for inclusion when reporting a Bayesian analysis of a clinical study
AU - Sung, Lillian
AU - Hayden, Jill
AU - Greenberg, Mark L.
AU - Koren, Gideon
AU - Feldman, Brian M.
AU - Tomlinson, George A.
N1 - Funding Information:
L.S. and J.H. are supported by Canadian Institutes of Health Research (CIHR) Post-doctoral Fellowships; L.S. is also supported by a Hospital for Sick Children Clinician Scientist Fellowship; M.G. holds the POGO Chair in Childhood Cancer Control; G.K. is a senior scientist at CIHR; and B.M.F. holds the Canada Research Chair in Childhood Arthritis. We wish to thank James G. Wright, MD, MPH, FRCSC, for his review and constructive criticism of an early draft of this manuscript. We also wish to thank the expert participants for their contribution.
PY - 2005/3
Y1 - 2005/3
N2 - Objective: (1) To generate a list of items that experts consider most important when reporting a Bayesian analysis of a clinical study, (2) to report on the extent to which we found these items in the literature, and (3) to identify factors related to the number of items in a report. Study Design and Setting: Based on opinions from 23 international experts, we determined the items considered most important when publishing a Bayesian analysis. We then performed a literature search to identify articles in which a Bayesian analysis was performed and determined the extent to which we found these items in each report. Finally, we examined the relationship between the number of items in a report and journal- and article-specific attributes. Results: Our final set of seven items described the prior distribution (specification, justification, and sensitivity analysis), analysis (statistical model and analytic technique), and presentation of results (central tendency and variance). There was >99% probability that more items were reported in studies with a noncontrolled study design and in journals with a methodological focus, lower impact factor, and absence of a word count limit. Conclusion: We developed a set of seven items that experts believe to be most important when reporting a Bayesian analysis.
AB - Objective: (1) To generate a list of items that experts consider most important when reporting a Bayesian analysis of a clinical study, (2) to report on the extent to which we found these items in the literature, and (3) to identify factors related to the number of items in a report. Study Design and Setting: Based on opinions from 23 international experts, we determined the items considered most important when publishing a Bayesian analysis. We then performed a literature search to identify articles in which a Bayesian analysis was performed and determined the extent to which we found these items in each report. Finally, we examined the relationship between the number of items in a report and journal- and article-specific attributes. Results: Our final set of seven items described the prior distribution (specification, justification, and sensitivity analysis), analysis (statistical model and analytic technique), and presentation of results (central tendency and variance). There was >99% probability that more items were reported in studies with a noncontrolled study design and in journals with a methodological focus, lower impact factor, and absence of a word count limit. Conclusion: We developed a set of seven items that experts believe to be most important when reporting a Bayesian analysis.
KW - Bayesian analysis
KW - Biostatistics
KW - Clinical studies
KW - Impact factor
UR - http://www.scopus.com/inward/record.url?scp=13844266733&partnerID=8YFLogxK
U2 - 10.1016/j.jclinepi.2004.08.010
DO - 10.1016/j.jclinepi.2004.08.010
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C2 - 15718115
AN - SCOPUS:13844266733
SN - 0895-4356
VL - 58
SP - 261
EP - 268
JO - Journal of Clinical Epidemiology
JF - Journal of Clinical Epidemiology
IS - 3
ER -