R: Generate Data to use in two-stage COMBO Functions

COMBO_data_2stage {COMBO}

R Documentation

Generate Data to use in two-stage COMBO Functions

Description

Generate Data to use in two-stage COMBO Functions

Usage

COMBO_data_2stage(
  sample_size,
  x_mu,
  x_sigma,
  z_shape,
  v_shape,
  beta,
  gamma,
  delta
)

Arguments

`sample_size`	An integer specifying the sample size of the generated data set.
`x_mu`	A numeric value specifying the mean of `x` predictors generated from a Normal distribution.
`x_sigma`	A positive numeric value specifying the standard deviation of `x` predictors generated from a Normal distribution.
`z_shape`	A positive numeric value specifying the shape parameter of `z` predictors generated from a Gamma distribution.
`v_shape`	A positive numeric value specifying the shape parameter of `v` predictors generated from a Gamma distribution.
`beta`	A column matrix of `\beta` parameter values (intercept, slope) to generate data under in the true outcome mechanism.
`gamma`	A numeric matrix of `\gamma` parameters to generate data under in the first-stage observation mechanism. In matrix form, the `gamma` matrix rows correspond to intercept (row 1) and slope (row 2) terms. The gamma parameter matrix columns correspond to the true outcome categories `Y \in \{1, 2\}`.
`delta`	A numeric array of `\delta` parameters to generate data under the second-stage observation mechanism. In array form, the `delta` matrix rows correspond to intercept (row 1) and slope (row 2) terms. The matrix columns correspond to first-stage observed outcome categories. The third dimension of the `delta` array is indexed by the true outcome categories.

Value

COMBO_data_2stage returns a list of generated data elements:

`obs_Ystar`	A vector of first-stage observed outcomes.
`obs_Ytilde`	A vector of second-stage observed outcomes.
`true_Y`	A vector of true outcomes.
`obs_Ystar_matrix`	A numeric matrix of indicator variables (0, 1) for the first-stage observed outcome `Y*`. Rows of the matrix correspond to each subject. Columns of the matrix correspond to each observed outcome category. Each row contains exactly one 0 entry and exactly one 1 entry.
`obs_Ytilde_matrix`	A numeric matrix of indicator variables (0, 1) for the second-stage observed outcome `Y*`. Rows of the matrix correspond to each subject. Columns of the matrix correspond to each observed outcome category. Each row contains exactly one 0 entry and exactly one 1 entry.
`x`	A vector of generated predictor values in the true outcome mechanism, from the Normal distribution.
`z`	A vector of generated predictor values in the first-stage observation mechanism from the Gamma distribution.
`v`	A vector of generated predictor values in the second-stage observation mechanism from the Gamma distribution.
`x_design_matrix`	The design matrix for the `x` predictor.
`z_design_matrix`	The design matrix for the `z` predictor.
`v_design_matrix`	The design matrix for the `v` predictor.

Examples

set.seed(123)
n <- 500
x_mu <- 0
x_sigma <- 1
z_shape <- 1
v_shape <- 1

true_beta <- matrix(c(1, -2), ncol = 1)
true_gamma <- matrix(c(.5, 1, -.5, -1), nrow = 2, byrow = FALSE)
true_delta <- array(c(1.5, 1, .5, .5, -.5, 0, -1, -1), dim = c(2, 2, 2))

my_data <- COMBO_data_2stage(sample_size = n,
                             x_mu = x_mu, x_sigma = x_sigma,
                             z_shape = z_shape, v_shape = v_shape,
                             beta = true_beta, gamma = true_gamma, delta = true_delta)
table(my_data[["obs_Ytilde"]], my_data[["obs_Ystar"]], my_data[["true_Y"]])

[Package COMBO version 1.0.0 Index]