NNTintervalsProspective
Produce Bayesian and classical intervals for NNT from observations in a prospective study. Useful for "anticipated results" when designing a study, The setting: patients will be tested immediately, and followed to determine the BestToTreat/BestToWait classification. as well as analyzing study results. There were (or will be) Npositives patients with a positive test, Nnegatives with a negative test. The observed NNTs in each group were (or will be) NNTpos and NNTneg.
NNTintervalsProspective(Npositives, Nnegatives, NtruePositives, NtrueNegatives, prev = 0.15, alpha = 0.025, prior = c(1/2, 1/2))
Npositives |
Total number of observed positives. |
Nnegatives |
Total number of observed negatives. |
NtruePositives |
Observed or anticipated number of "BestToTreat" among the positives. |
NtrueNegatives |
Observed or anticipated number of "BestToWait" among the negatives. |
prev |
= 0.15 Prevalence of "BestToTreat" characteristic. |
alpha |
= 0.025 Significance level (one side). |
prior |
Beta parameters for prior. Default is the Jeffreys prior = c(1/2,1/2). Jaynes prior = c(0,0) won't work when #fp=1. |
The Bayesian predictive intervals for NNTpos and NNTneg. These are obtained from predictive intervals for PPV and NPV, based on Jeffreys' beta(1/2,1/2) prior.
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