Free Statistical software: Shakespeare's Confidence Calculator v1.0
Whether doctor or patient, deciding on what constitutes the best treatment for a particular disease is often based on published medical literature. How medical studies are reported, and the methods used to interpret results, all play vital roles in medical decision-making.
One way that we believe results in improving the reporting of results, leading to less chance of misinterpretation and more informed decisions, is by use of confidence levels, clinical significance curves, and confidence contours. These methods have been published previously:
Shakespeare TP, Gebski VJ, Veness MJ, Simes J. Improving interpretation of clinical studies by use of confidence levels, clinical significance curves, and risk-benefit contours. Lancet. 2001: 357: 1349-53.
In brief, they allow the reader of a study (whether doctor or patient), to know the confidence (or probability) that one treatment is better than another, and by how much. They also can show the confidence that a treatment does not have excessive side-effects. For a discussion of the pros and cons of confidence intervals vs confidence levels, clinical significance curves and risk-benefit contours, go to my confidence interval page, or my Statistics Supercourse lecture hosted by the University of Pittsburgh. For a discussion of current randomized studies and the PRIMER Collaboration, go to my PRIMER page. or the PRIMER Collaboration site. The PRIMER Collaboration has conducted two randomized studies, of over 300 specialist doctors, to determine which combination of p values, 95% confidence intervals and confidence levels is superior for result interpretation. Participant doctors include clinicians, researchers, journal reviewers and editors, and readers of the medical literature. The studies found that confidence levels are superior to p values and 95% confidence intervals: doctors interpreted results better, with a resultant improvement in clinical practice. All researchers should incorporate confidence levels into research findings.
The results are published:
Shakespeare TP, Gebski V, Tang J, Lim K, Lu JJ, Zhang X, Jiang G. Influence of the way results are presented on research interpretation and medical decision making: the PRIMER collaboration randomized studies. Med Decis Making. 2008; 28(1): 127-37. The abstract is available here.
The following free statistical software consists of an Excel spreadsheet, and is downloadable free of charge. Instructions for and conditions of use are described on the "INSTRUCTIONS" sheet inside. The spreadsheet calulates confidence levels, confidence intervals, clinical significance curves and risk-benefit contours.
Conditions of use: you must agree to the following before you proceed!
By using this free ststistical software you agree to reference the use of Shakespeare's confidence levels, clinical significance curves, and risk-benefit contours in any manuscript submitted for publication, by referencing our original publications which describe these decision-making tools:
Shakespeare TP, Gebski VJ, Veness MJ, Simes J. Improving the interpretation of clinical studies by use of confidence levels, clinical significance curves, and risk-benefit contours. Lancet 2001; 357: 1349-1353.
Shakespeare TP, Gebski V, Tang J, Lim K, Lu JJ, Zhang X, Jiang G. Influence of the way results are presented on research interpretation and medical decision making: the PRIMER collaboration randomized studies. Med Decis Making. 2008; 28(1): 127-37.
You also agree that the authors do not guarantee the accuracy of the numbers or figures obtained from this calculator and that you will not hold us liable for any losses (monetary, psychological, professional or otherwise) or grievances arising from the use of this calculator. All data that you obtain should be checked by an appropriately qualified statistician with reference to our article above. For further information and provision of feedback, please contact Dr. Shakespeare. This free statistical software is for personal use only and is not to be sold, lent, distributed, copied or modified in any way.
A/Prof. Thomas Philip Shakespeare
