Report summary statistics for diagnostic tests compared to true disease status ------------------------------------------------------------------------------
^diagt^ diagvar testvar [weight] [^if^ exp] [^in^ range] [^,^ ^prev(^#^ > )^ ^level(^#^)^ ^sf^ ^sf0^ ^notable^ ^woolf^ ^tb^ ^bamber^ ^hanley^ odds tabula > te_options]
^diagti^ #a #b #c #d [^,^ ^prev(^#^)^ ^level(^#^)^ ^sf^ ^sf0^ ^notable^ ^woolf^ ^tb^ ^bamber^ ^hanley^ odds tabula > te_options]
^fweight^s are allowed with ^diagt^; see help @weights@.
Description -----------
^diagt^ displays various summary statistics for a diagnostic test, compared to patients' true disease status, sensitivity, specificity, and predictive values, from a 2x2 table. ^diagti^ is the immediate version. #a #b #c #d are, respectively, the numbers of true positives (diseased subjects with correct positive test results), false negatives (disease, but negative test), false positives (no disease, but positive test) and true negatives (no disease, negative test).
Sensitivity (sens.) is the proportion of diseased patients correctly identified > = a/(a+b). Specificity (spec.) is the proportion of healthy patients correctly identified = d/(c+d). The ROC (Receiver Operating Characteristic curve) area is (for a simple test) the average of sensitivity and specificity.
The likelihood ratio of a positive test (LR+) is the ratio of the probability (likelihood) of a positive test result in an abnormal patient and in a normal patient = Sensitivity/(1- specificity). Multiplying the prior odds of disease by LR+ gives the odds of disease following a positive tes > t. The lilkelihood ratio of a negative test (LR-) works in the same way.
The odds ratio (OR), defined as A/B/(C/D) in the usual way, is also equal to LR+/LR-.
The positive and negative predictive values (PPV & NPV) show the probability of > the patient having the disease following a + or a - test. If no prevalence is given, the sample is assumed to be a cohort and PPV & NPV are respectively the proportions of test positives and test negatives that are correct = a/(a+c) and d/(b+d). Otherwise, they are calculated using the likelihood ratios, and assuming the given prevalence is correct.
diagvar is the variable which contains the real status of the patient, and testvar is the variable which identifies the result of the diagnostic test. testvar and diagvar can have only two nonmissing values. The higher value must identify the positive result of the test or the diseased status of the patient.
All confidence intervals are based on standard Stata commands: For Sensitivity, Specificity, PPV & NPV (except with the prevalence option), exact binomial confidence intervals are given, (command @ci@). ROC area uses @roctab@. LR+ & LR- (based on risk ratio) and odds ratio all use command @cs@.
Options -------
^prev(^#^)^ specifies the estimated prevalence of the disease, either as a deci > mal or as a percentage with % sign. This is used in estimating the positive an > d negative predicted values, based on Bayes' theorem. If the ^prev^ option is used, confidence intervals for PPV and NPV are found as below.
Prior odds = Prev/(1-Prev.)
Odds following +ve test = Prior odds * LR+
PPV = Odds following +ve test/(1 - Odds following +ve test)
Odds following -ve test = Prior odds * LR-
NPV = Odds following -ve test/(1 - Odds following -ve test)
Confidence intervals are found using the upper & lower bounds of LR+ & LR- Posterior odds and are converted to probabilties as Probability = Odds/((1 + odds)
^sf^ and ^sf0^ do essentially the same thing: Likelihood ratios are cacluated using the substitution formula instead of by the standard method. 0.5 is added to all cell frequencies before calculation. Conidence intervals for risk ratios and odds ratios are based on the delta method. With ^sf0^ the substitution formula is used only when there is a zero in one or more cell. ^sf^ overrides ^tb^ and ^woolf^.
^odds^ asks for the likelihood of a positive results to be represented as odds, > with their confidence intervals. Please note: these are the odds corresponding > to the prevalence, the PPV and (100%-NPV).
^level(^#^)^ specifies the confidence level, in percent, for calculation of confidence intervals of the sensitivity, specificity, predictive values, and prevalence. The default is ^level(95)^ or as set by ^set level^.
^noTable^ suppresses the contingency table, but shows the other results. ^tb^ produces test-based confidence intervals for the likelihood ratios and odds ratio.
^woolf^ uses the Woolf formula for the odds ratio, overriding ^tb^.
^bamber^ and ^hanley^ use the Bamber and Hanley options for calculating the ROC > areas.
Examples --------
. ^diagt truediag test [fw=n]^ . ^diagt truediag test, [fw=n] prev(25)^ . ^diagt truediag test, [fw=n] level(99) chi^
. ^diagti 80 17 11 44^, or
Author ------
Paul T Seed (Paul.Seed@@kcl.ac.uk) Maternal & Fetal Research Unit, GKT School of Medicine, KCL North Wing, St Thomas' Hospital, Lambeth Palace Road, London SE1 7EH
Developed from ^diagtest^ by Aurelio Tobias (STB-56: sbe36) Aurelio Tobias Hospital de la Santa Creu i Sant Pau, Barcelona, Spain. Email: atobias@@cocrane.es
Additional material from Tom Steichen
Also see --------
Manual: ^[R] tabulate, [R] lstat, [R] lsens, [R] roc, [R] ci^ On-line: help for @tabulate@, @weights@, @ci@, @cs@, @roc@.