pistar_compute {COMBO} R Documentation

## Compute Conditional Probability of Each Observed Outcome Given Each True Outcome, for Every Subject

### Description

Compute Conditional Probability of Each Observed Outcome Given Each True Outcome, for Every Subject

### Usage

pistar_compute(gamma, Z, n, n_cat)


### Arguments

 gamma A numeric matrix of regression parameters for the observed outcome mechanism, Y* | Y (observed outcome, given the true outcome) ~ Z (misclassification predictor matrix). Rows of the matrix correspond to parameters for the Y* = 1 observed outcome, with the dimensions of Z. Columns of the matrix correspond to the true outcome categories j = 1, \dots, n_cat. Z A numeric design matrix. n An integer value specifying the number of observations in the sample. This value should be equal to the number of rows of the design matrix, Z. n_cat The number of categorical values that the true outcome, Y, and the observed outcome, Y* can take.

### Value

pistar_compute returns a matrix of conditional probabilities, P(Y_i^* = k | Y_i = j, Z_i) = \frac{\text{exp}\{\gamma_{kj0} + \gamma_{kjZ} Z_i\}}{1 + \text{exp}\{\gamma_{kj0} + \gamma_{kjZ} Z_i\}} for each of the i = 1, \dots, n subjects. Rows of the matrix correspond to each subject and observed outcome. Specifically, the probability for subject i and observed category $1$ occurs at row i. The probability for subject i and observed category $2$ occurs at row i + n. Columns of the matrix correspond to the true outcome categories j = 1, \dots, n_cat.

[Package COMBO version 1.0.0 Index]