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This guide is designed to summarize key notation and quantities used the COMMA R Package and associated publications.

Term Definition Description
\(X\) – Predictor matrix for the true mediator and outcome.
\(C\) – Covariate matrix for the true mediator and outcome.
\(Z\) – Predictor matrix for the observed mediator, conditional on the true mediator
\(Y\) – Outcome variable.
M \(M \in \{1, 2\}\) True binary mediator. Reference category is 2.
\(m_{ij}\) \(\mathbb{I}\{M_i = j\}\) Indicator for the true binary mediator.
\(M^*\) \(M^* \in \{1, 2\}\) Observed binary mediator. Reference category is 2.
\(m^*_{i \ell}\) \(\mathbb{I}\{M^*_i = \ell \}\) Indicator for the observed binary mediator.
True Mediator Mechanism \(\text{logit} \{ P(M = 1 | X, C ; \beta) \} = \beta_{0} + \beta_{X} X + \beta_{C} C\) Relationship between \(X\) and \(C\) and the true mediator, \(M\).
Observed Mediator Mechanism \(\text{logit}\{ P(M^* = 1 | M = m, Z ; \gamma) \} = \gamma_{1m0} + \gamma_{1mZ} Z\) Relationship between \(Z\) and the observed mediator, \(M^*\), given the true mediator \(M\).
Outcome Mechanism \(E(Y| X, C, M ; \theta) \} = \theta{0} + \theta_{X} X + \theta_{C} C \theta_{M}M + \theta_{XM}XM\) Relationship between \(X\), \(C\), and \(M\) and the outcome of interest \(Y\).
\(\pi_{ij}\) \(P(M_i = j | X, C ; \beta) = \frac{\text{exp}\{\beta_{j0} + \beta_{jX} X_i + \beta_{jC} C_i\}}{1 + \text{exp}\{\beta_{j0} + \beta_{jX} X_i + \beta_{jC} C_i\}}\) Response probability for individual \(i\)’s true mediator category.
\(\pi^*_{i \ell j}\) \(P(M^*_i = \ell | M_i = j, Z ; \gamma) = \frac{\text{exp}\{\gamma_{\ell j 0} + \gamma_{ \ell jZ} Z_i\}}{1 + \text{exp}\{\gamma_{\ell j0} + \gamma_{kjZ} Z_i\}}\) Response probability for individual \(i\)’s observed mediator category, conditional on the true mediator.
\(\pi^*_{i \ell}\) \(P(M^*_i = \ell | M_i, X, Z ; \gamma) = \sum_{j = 1}^2 \pi^*_{i \ell j} \pi_{ij}\) Response probability for individual \(i\)’s observed mediator cateogry.
\(\pi^*_{jj}\) \(P(M^* = j | M = j, Z ; \gamma) = \sum_{i = 1}^N \pi^*_{ijj}\) Average probability of correct classification for category \(j\).
Sensitivity \(P(M^* = 1 | M = 1, Z ; \gamma) = \sum_{i = 1}^N \pi^*_{i11}\) True positive rate. Average probability of observing mediator \(k = 1\), given the true mediator \(j = 1\).
Specificity \(P(M^* = 2 | M = 2, Z ; \gamma) = \sum_{i = 1}^N \pi^*_{i22}\) True negative rate. Average probability of observing mediator \(k = 2\), given the true mediator \(j = 2\).
\(\beta_X\) – Association parameter of interest in the true mediator mechanism.
\(\gamma_{11Z}\) – Association parameter of interest in the observed mediator mechanism, given \(j=1\).
\(\gamma_{12Z}\) – Association parameter of interest in the observed mediator mechanism, given \(j=2\).
\(\theta_X\) – Association parameter of interest in the outcome mechanism.
\(\theta_M\) – Association parameter relating the true mediator to the outcome.
\(\theta_{XM}\) – Association parameter for the interaction between \(X\) and \(M\) in the outcome mechanism.