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Clinical Trialist |
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| この情報はストアのものより古い可能性がございます。 | ||||
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価格 | 無料 | ダウンロード |
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|---|---|---|---|---|
| ｼﾞｬﾝﾙ | メディカル | |||
サイズ | 641.8KB | |||
| 開発者 | Robert Goodman | |||
| 順位 |
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| ﾘﾘｰｽ日 | 2012-10-25 08:53:35 | 評価 | 評価が取得できませんでした。 | |
| 互換性 | iOS 4.3以降が必要です。 iPhone、iPad および iPod touch 対応。 | |||
Bayesian Clinical Trialist: Not Just another post-test probability calculator!
•Are you tired of misinterpreting p-values and 95% confidence intervals?
•Have you longed for the day when you could estimate the probability that the null
hypothesis is true—rather than the probability of the study result under the null
hypothesis?
•Have you experienced Bayesian urges but never known quite how to express them?
Well, look no further. Now you too can interpret randomized trials like a Bayesian!
Bayesian Clinical Trialist combines the user’s “prior” with study results to produce a genuine posterior estimate of the measure of effect. The user simply enters the randomized trial result (e.g., relative risk, odds ratio, hazard ratio, or absolute risk reduction or increase), the 95% confidence
interval, the user’s prior estimate, and the user’s prior “confidence region.” Bayesian Clinical Trialist then calculates the posterior estimate, 95% “credible interval,” and “Bayesian p-value” (the probability the treatment is ineffective or harmful). Bayesian Clinical Trialist is intended for clinicians who are interested in moving beyond sensitivity and specificity to the Bayesian interpretation of clinical trial results. The Trialist is especially intended for those interested in teaching these methods to physicians and other health care practitioners, trainees, and students. The app makes it possible to demonstrate how clinical trial results may be affected by prior estimates, and enables the user to “experiment” with various priors and to see how impact posterior estimates.
Also included is a brief tutorial on conditional probability, Bayes’ theorem, and its application to diagnostic tests, clinical trials, and anything else for that matter!
Feedback is welcome: Bayesianclinicaltrialist@gmail.com
更新履歴
What's New in this Version
--Calculation of “Bayesian p-value”
--Bug fixes
•Are you tired of misinterpreting p-values and 95% confidence intervals?
•Have you longed for the day when you could estimate the probability that the null
hypothesis is true—rather than the probability of the study result under the null
hypothesis?
•Have you experienced Bayesian urges but never known quite how to express them?
Well, look no further. Now you too can interpret randomized trials like a Bayesian!
Bayesian Clinical Trialist combines the user’s “prior” with study results to produce a genuine posterior estimate of the measure of effect. The user simply enters the randomized trial result (e.g., relative risk, odds ratio, hazard ratio, or absolute risk reduction or increase), the 95% confidence
interval, the user’s prior estimate, and the user’s prior “confidence region.” Bayesian Clinical Trialist then calculates the posterior estimate, 95% “credible interval,” and “Bayesian p-value” (the probability the treatment is ineffective or harmful). Bayesian Clinical Trialist is intended for clinicians who are interested in moving beyond sensitivity and specificity to the Bayesian interpretation of clinical trial results. The Trialist is especially intended for those interested in teaching these methods to physicians and other health care practitioners, trainees, and students. The app makes it possible to demonstrate how clinical trial results may be affected by prior estimates, and enables the user to “experiment” with various priors and to see how impact posterior estimates.
Also included is a brief tutorial on conditional probability, Bayes’ theorem, and its application to diagnostic tests, clinical trials, and anything else for that matter!
Feedback is welcome: Bayesianclinicaltrialist@gmail.com
更新履歴
What's New in this Version
--Calculation of “Bayesian p-value”
--Bug fixes
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