Bayesian Statistics I MultiCalc

 

Input
 

Prevalence		% fraction ratio
Sensitivity		% fraction ratio
Specificity		% fraction ratio

 

Results
 

True Pos		% fraction ratio
False Pos		% fraction ratio
True Neg		% fraction ratio
False Neg		% fraction ratio
Pos Pred Value		% fraction ratio
Neg Pred Value		% fraction ratio
LR Pos		% fraction ratio
LR Neg		% fraction ratio
Pre Test Odds		% fraction ratio
Post Odds Pos		% fraction ratio
Post Prob Pos		% fraction ratio
Post Odds Neg		% fraction ratio
Post Prob Neg		% fraction ratio
False Pos Rate		% fraction ratio
False Neg Rate		% fraction ratio
Overall Acc		% fraction ratio
Decimal Precision   0 1 2 3

 

 

 
Equations used
 

TruePos = Sensitivity * Prevalence

FalsePos = (1 - Specificity) * (1 - Prevalence)

TrueNeg = Specificity * (1 - Prevalence)

FalseNeg = (1 - Sensitivity) * Prevalence

PosPredValue = 100 * TruePos / (TruePos + FalsePos)

NegPredValue = 100 * TrueNeg / (TrueNeg + FalseNeg)

LRPos = Sensitivity / (1-Specificity)

LRNeg = (1-Sensitivity) / Specificity

PreTestOdds = Prevalence / (1 - Prevalence)

PostOddsPos = PreTestOdds * LRPos

PostProbPos = PostOddsPos / (1 + PostOddsPos)

PostOddsNeg = PreTestOdds * LRNeg

PostProbNeg = PostOddsNeg / (1 + PostOddsNeg)

FalsePosRate = 100 * FalsePos / (FalsePos + TrueNeg)

FalseNegRate = 100 * FalseNeg / (TruePos + FalseNeg)

OverallAcc = 100 * (TruePos + TrueNeg)

 

 

References

1. Perera R, Heneghan C. Making sense of diagnostic test likelihood ratios. ACP J Club. 2007 Mar-Apr;146(2):A8-9. PubMed ID: 17335149
2. Page J, Attia J. Using Bayes' nomogram to help interpret odds ratios. ACP J Club. 2003 Sep-Oct;139(2):A11-2. PubMed ID: 12954046