The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

COMBO Notation Guide

Kim Hochstedler

Notation

This guide is designed to summarize key notation and quantities used the COMBO R Package and associated publications.
Term Definition Description
\(X\) Predictor matrix for the true outcome.
\(Z\) Predictor matrix for the observed outcome, conditional on the true outcome.
\(Y\) \(Y \in \{1, 2\}\) True binary outcome. Reference category is 2.
\(y_{ij}\) \(\mathbb{I}\{Y_i = j\}\) Indicator for the true binary outcome.
\(Y^*\) \(Y^* \in \{1, 2\}\) Observed binary outcome. Reference category is 2.
\(y^*_{ik}\) \(\mathbb{I}\{Y^*_i = k\}\) Indicator for the observed binary outcome.
True Outcome Mechanism \(\text{logit} \{ P(Y = j | X ; \beta) \} = \beta_{j0} + \beta_{jX} X\) Relationship between \(X\) and the true outcome, \(Y\).
Observation Mechanism \(\text{logit}\{ P(Y^* = k | Y = j, Z ; \gamma) \} = \gamma_{kj0} + \gamma_{kjZ} Z\) Relationship between \(Z\) and the observed outcome, \(Y^*\), given the true outcome \(Y\).
\(\pi_{ij}\) \(P(Y_i = j | X ; \beta) = \frac{\text{exp}\{\beta_{j0} + \beta_{jX} X_i\}}{1 + \text{exp}\{\beta_{j0} + \beta_{jX} X_i\}}\) Response probability for individual \(i\)’s true outcome category.
\(\pi^*_{ikj}\) \(P(Y^*_i = k | Y_i = j, Z ; \gamma) = \frac{\text{exp}\{\gamma_{kj0} + \gamma_{kjZ} Z_i\}}{1 + \text{exp}\{\gamma_{kj0} + \gamma_{kjZ} Z_i\}}\) Response probability for individual \(i\)’s observed outcome category, conditional on the true outcome.
\(\pi^*_{ik}\) \(P(Y^*_i = k | Y_i, X, Z ; \gamma) = \sum_{j = 1}^2 \pi^*_{ikj} \pi_{ij}\) Response probability for individual \(i\)’s observed outcome cateogry.
\(\pi^*_{jj}\) \(P(Y^* = j | Y = j, Z ; \gamma) = \sum_{i = 1}^N \pi^*_{ijj}\) Average probability of correct classification for category \(j\).
Sensitivity \(P(Y^* = 1 | Y = 1, Z ; \gamma) = \sum_{i = 1}^N \pi^*_{i11}\) True positive rate. Average probability of observing outcome \(k = 1\), given the true outcome \(j = 1\).
Specificity \(P(Y^* = 2 | Y = 2, Z ; \gamma) = \sum_{i = 1}^N \pi^*_{i22}\) True negative rate. Average probability of observing outcome \(k = 2\), given the true outcome \(j = 2\).
\(\beta_X\) Association parameter of interest in the true outcome mechanism.
\(\gamma_{11Z}\) Association parameter of interest in the observation mechanism, given \(j=1\).
\(\gamma_{12Z}\) Association parameter of interest in the observation mechanism, given \(j=2\).

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.