About Anaconda Help Download Anaconda

r / packages / r-comparetests

A standard test is observed on all specimens. We treat the second test (or sampled test) as being conducted on only a stratified sample of specimens. Verification Bias is this situation when the specimens for doing the second (sampled) test is not under investigator control. We treat the total sample as stratified two-phase sampling and use inverse probability weighting. We estimate diagnostic accuracy (category-specific classification probabilities; for binary tests reduces to specificity and sensitivity, and also predictive values) and agreement statistics (percent agreement, percent agreement by category, Kappa (unweighted), Kappa (quadratic weighted) and symmetry tests (reduces to McNemar's test for binary tests)). See: Katki HA, Li Y, Edelstein DW, Castle PE. Estimating the agreement and diagnostic accuracy of two diagnostic tests when one test is conducted on only a subsample of specimens. Stat Med. 2012 Feb 28; 31(5) <doi:10.1002/sim.4422>.

Click on a badge to see how to embed it in your web page
badge
https://anaconda.org/r/r-comparetests/badges/version.svg
badge
https://anaconda.org/r/r-comparetests/badges/latest_release_date.svg
badge
https://anaconda.org/r/r-comparetests/badges/latest_release_relative_date.svg
badge
https://anaconda.org/r/r-comparetests/badges/platforms.svg
badge
https://anaconda.org/r/r-comparetests/badges/license.svg
badge
https://anaconda.org/r/r-comparetests/badges/downloads.svg

© 2025 Anaconda, Inc. All Rights Reserved. (v4.0.7) Legal | Privacy Policy