The Journal of Bone and Joint Surgery (American). 2010;92:1732-1737.
doi:10.2106/JBJS.I.00724
© 2010 The Journal of Bone and Joint Surgery, Inc.
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Statistical Consideration for Bilateral Cases in Orthopaedic Research

Moon Seok Park, MD1, Sung Ju Kim, MS2, Chin Youb Chung, MD1, In Ho Choi, MD3, Sang Hyeong Lee, MD1 and Kyoung Min Lee, MD1

1 Department of Orthopaedic Surgery, Seoul National University Bundang Hospital, 300 Gumi-Dong, Bundang-Gu, Sungnam, Kyungki 463-707, South Korea. E-mail address for K.M. Lee: oasis100{at}empal.com
2 Health Economics and Outcome Research, Market Access, Novartis Korea, 84-11 Namdaemun 5th Street, Chung-Gu, Seoul 100-753, South Korea
3 Department of Orthopaedic Surgery, Seoul National University Children's Hospital, 28 Yongun-Dong, Chongno-Gu, Seoul 110-744, South Korea

Investigation performed at Seoul National University Bundang Hospital, Sungnam, Kyungki, South Korea

Disclosure: The authors did not receive any outside funding or grants in support of their research for or preparation of this work. Neither they nor a member of their immediate families received payments or other benefits or a commitment or agreement to provide such benefits from a commercial entity.

Background Statistical independence means that one observation is not affected by another; however, the principle of statistical independence is violated if left and right-side measures within a subject are considered to be independent, because they are usually correlated and can affect each other. The purpose of the present study was to analyze the violation of statistical independence in recent orthopaedic research papers and to demonstrate the effect of statistical analysis that considered the data dependency within a subject.

Methods First, all original articles that had been published in The Journal of Bone and Joint Surgery (American Volume) over a two-year period were evaluated. The analysis was designed to identify articles that included bilateral cases and possible violations of statistical independence. Second, a demonstrative logistic regression without consideration of statistical independence was performed and was compared with a statistical analysis that considered data dependency within a subject. Radiographs of 1200 hips in 600 patients were used to examine the differences in terms of odds ratios (with 95% confidence intervals) of the risk factors for hip osteoarthritis.

Results Four hundred and eighty-six original articles were reviewed, and 151 articles (including forty-one articles involving the hip, thirty-four involving the knee, twenty-one involving the foot or ankle, nineteen involving the shoulder, ten involving the hand or wrist, nine involving the elbow, and seventeen involving other structures) were considered to include bilateral cases. Of the 486 articles that were reviewed, 120 articles (25%) (including thirty-six articles involving the hip, twenty-six involving the knee, fifteen involving the foot or ankle, fourteen involving the shoulder, seven involving the elbow, six involving the hand or wrist, and sixteen involving other structures) were found to have possibly violated statistical independence. Demonstrative statistical analysis showed that logistic regression was not robust to the violation of statistical independence. The 95% confidence intervals of the odds ratios for the risk factors showed narrower ranges (1.13 to 2.68 times) when data dependency within a subject was not considered.

Conclusions Researchers need to consider statistical independence when performing statistical analysis, particularly in studies involving bilateral cases. If data dependency within a subject is not considered, studies involving bilateral cases can bias results, depending on the context of those studies.


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Letters to the Editor:

Read all Letters to the Editor

GEE and Multilevel Models
Chao-Pin Chen, et al.
JBJS Online, 1 Sep 2010 [Full text]
Dr. Lee and colleagues respond to Drs. Chen and Lin
Kyoung Min Lee, MD, et al.
JBJS Online, 1 Sep 2010 [Full text]