ci.pv: Confidence intervals for positive and negative predictive...

In statpsych: Statistical Methods for Psychologists

Confidence intervals for positive and negative predictive values with retrospective sampling

Description

Computes adjusted Wald confidence intervals for positive and negative predictive values (PPV and NPV) of a diagnostic test with retrospective sampling where the population prevalence rate is assumed to be known. With retrospective sampling, one random sample is obtained from a subpopulation that is known to have a "positive" outcome, a second random sample is obtained from a subpopulation that is known to have a "negative" outcome, and then the diagnostic test (scored "pass" or "fail") is given in each sample. PPV and NPV can be expressed as a function of proportion ratios and the known population prevalence rate (the population proportion who would "pass"). The confidence intervals for PPV and NPV are based on the Price-Bonett adjusted Wald confidence interval for a proportion ratio.

Usage

ci.pv(alpha, f1, f2, n1, n2, prev)

Arguments

alpha	alpha level for 1-alpha confidence
f1	number of participants with a positive outcome who pass the test
f2	number of participants with a negative outcome who fail the test
n1	sample size for the positive outcome group
n2	sample size for the negative outcome group
prev	known population proportion with a positive outcome

Value

Returns a 2-row matrix. The columns are:

• Estimate - adjusted estimate of the predictive value

• LL - lower limit of the adjusted Wald confidence interval

• UL - upper limit of the adjusted Wald confidence interval

References

\insertRef

Price2008statpsych

Examples

ci.pv(.05, 89, 5, 100, 100, .16)

# Should return:
#        Estimate        LL        UL
# PPV:  0.7640449 0.5838940 0.8819671
# NPV:  0.9779978 0.9623406 0.9872318

statpsych documentation built on Sept. 11, 2024, 7:42 p.m.