## EpiMax Table Calculator

### Epidemiology & Lab Statistics from Study Counts With Chi Square, NNT & "Cost to Treat" Estimates

[For Demonstration Only-Not for Official Use]
 Clinical & Economic Software Solutions Health Decision Strategies, LLC Princeton, New Jersey  USA Data Entry Page Instructions: Using 2x2 study data, you can change the "Title" and  fill in the four center cells in the table below (the cells in blue)  and if you wish, enter a "Cost Per Person" value. Hit the "Calculate" button to see the estimated results. (Results generated will appear in the boxes outside and below the center cells.)

 Target Disorder or Outcome Analysis Title: Present Absent Case Control True Posititve(a) False Positive(b) a + b RxDxH Control Group Diag. Test positive Exposed to Risk Factor False Negative(c) True Negative(d) c + d RxDxH -- Experimental Group-- Diag. Test negative-- Not Exposed to Risk Incremental Cost Per Person (CPP) Per Duration a + c b + d a+b+c+d \$

After you enter values into the four blue center cells above,
press the "Calculate" button, to see the estimates
.

 Other names: Sensitivity a/(a+c) True positive rate Specifity d/(b+d) True negative rate Likelihood Ratio + a/(a+c)/(b/b+d) sensitivity/(1-spec) Likelihood Ratio - c/(a+c)/(d/b+d) (1-sensit)/specificity False positive rate b/(b+d) 1-specificity False negative rate c/(a+c) 1-sensitivity Probability of disease (a+c)/(a+b+c+d) Prevalence Predictive value positive a/(a+b) Bayes' Theorem * p(pos test wrong) b/(a+b) Predictive value negative d/(c+d) p(neg test wrong) c/(c+d) p(test positive) (a+b)/(a+b+c+d) Will test be positive? p(test negative) (c+d)/(a+b+c+d) Complement of P(tp) Overall accuracy (a+d)/(a+b+c+d) Probability correct Relative Risk (a/(a+b))/(c/(c+d)) Risk without Rx / Risk with Rx Odds Ratio (a/c) /(b/d) = (ad)/(cb) See note below Attributable Risk (a/(a+b))-(c/(c+d)) Risk with exposure minus risk without. NNT 1/(a/(a+b))-(c/(c+d)) Number needed to treat Cost to Treat CPP x NNT Cost for one improvement

 Chi Square d.f. p
 Statistic Value Low 95% CI Hi 95% CI Odds Ratio Relative Risk Kappa Sensitivity Specificity Pos Pred Val Neg Pred Val

### Chi-Square Statistics and Confidence Intervals

The Chi-Square section above estimates various additional statistics from a 2-by-2 table. It estimates a Yates-corrected chi-square, along with confidence intervals for other quantities relevant to two special kinds of 2-by-2 tables:
1. analysis of risk factors for unfavorable outcomes (odds ratio, relative risk)
2. analysis of the effectiveness of a diagnostic criterion for some conditions (sensitivity, specificity, positive predictive value, negative predictive value)

These concepts are explained in detail in an online Evidence-based Medicine Glossary. Confidence intervals for the estimated parameters are computed by a general method given in: Statistical Methods for Rates and Proportions (2nd Ed.) by Joseph L. Fleiss (Pub: John Wiley & Sons, New York, 1981).

Relative Risk: If 2x2 data is from a cohort study (prospective), then use the Relative Risk value which is the ratio of the rate of events in the control (unexposed) group "a/a+b" to the rate of  events in the experimental (exposed)  group "c/c+d".

Odds Ratio: If 2x2 data is from a case-control study, then use the Odds Ratio value which is the ratio of the odds of  disease for the experimental group over the odds of disease for the control group.  Or the ratio of the odds of being exposed or unexposed in the "case" group "a/c" to the odds of being exposed or unexposed the "control" group "b/d".