--- title: "Using diagcounts" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Using diagcounts} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ## Motivation Diagnostic accuracy studies frequently report summary measures such as sensitivity, specificity, predictive values, and prevalence, but omit the underlying 2×2 table counts (true positives, false negatives, false positives, and true negatives). These counts are often required for downstream analyses, including meta-analysis, decision modeling, and health economic evaluation. The **diagcounts** package implements a system of linear equations to recover these unreported counts when a sufficient set of accuracy measures is available. --- ## Basic usage The primary function is `derive_counts()`. Users supply the total sample size and any combination of reported diagnostic accuracy measures that uniquely identify the underlying 2×2 table. ```r library(diagcounts) res <- derive_counts( n = 105, sensitivity = 0.6, specificity = 0.893, prevalence = 0.733 ) res ``` The function returns integer-valued counts: ```r as.table(res) ``` --- ## Alternative combinations of inputs Any identifiable combination of accuracy measures may be used. For example, counts can also be recovered using predictive values: ```r derive_counts( n = 200, sensitivity = 0.75, ppv = 0.82, npv = 0.70 ) ``` Internally, the package constructs and solves a system of linear equations corresponding to the supplied measures. --- ## Infeasible systems If the supplied measures do not uniquely identify a valid 2×2 table, or if the resulting system is mathematically inconsistent, `derive_counts()` will stop with an error: ```r # Not enough information # derive_counts(n = 100, sensitivity = 0.8) ``` This behavior is intentional and ensures that returned counts are both mathematically and epidemiologically valid. --- ## Discussion The methods implemented in `diagcounts` focus on settings in which the system of equations is exactly identified and yields a unique integer solution. Extensions to partially identified systems and bound-based solutions, as discussed in the accompanying paper, may be considered in future versions of the package. ## References Xie X, Wang M, Antony J, Vandersluis S, Kabali CB (2025). *System of Linear Equations to Derive Unreported Test Accuracy Counts*. Statistics in Medicine. https://doi.org/10.1002/sim.70336