COMBO

Use frequentist and Bayesian methods to estimate parameters from a binary outcome misclassification model. These methods correct for the problem of "label switching" by assuming that the sum of outcome sensitivity and specificity is at least 1. A description of the analysis methods is available in Hochstedler and Wells (2023) doi:10.48550/arXiv.2303.10215.

Last 30 days

This package has been downloaded 483 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 49 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 4,200 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Feb 20, 2025 with 53 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.