sim.mp {binGroup}R Documentation

Simulation Function for Group Testing Data with Matrix Pooling Design

Description

Simulates data in group testing form ready to be fit by gtreg.mp.

Usage

sim.mp(gshape = 20, gscale = 2, beta.par, rown, coln,
 sens = 1, spec = 1, sens.ind = NULL, spec.ind = NULL)

Arguments

gshape shape parameter of gamma distribution, must be non-negative, set to be 20 by default
gscale scale parameter of gamma distribution, must be strictly positive, set to be 2 by default
beta.par the true coefficients in the linear predictor
rown a vector that specifies the number of rows in each matrix, a scalar if only one matrix is simulated
coln a vector that specifies the number of columns in each matrix, a scalar if only one matrix is simulated
sens sensitivity of the group tests, set to be 1 by default.
spec specificity of the group tests, set to be 1 by default.
sens.ind sensitivity of the individual retests, set to be equal to sens if not specified otherwise.
spec.ind specificity of the individual retests, set to be equal to spec if not specified otherwise.

Details

sim.mp generates group testing data in matrix pooling form. To begin, the covariates are generated from a gamma distribution with given gshape and gscale. The individual probabilities are calculated with these covariates and the logit link using coefficients given in beta.par. The true individual responses are simulated next using Bernoulli distributions with these corresponding individual probabilities. The individuals are organized into (by column) one or more matrices specified by rown and coln, and the true group responses are found (i.e., if at least one response is positive, the group is positive; otherwise, the group response is negative). The row and column group responses are simulated from Bernoulli distributions using the given sens and spec values. Results of individual retests are simulated with sens.ind and spec.ind for individuals that lie on the intersection of an observed positive row and an observed positive column. In the case where no column (row) tests positive in a matrix, all the individuals in any observed positive rows (columns) will be assigned a simulated retest result.

Value

sim.mp returns a list with the components dframe: the data frame that is actually to be fit, ind: the true individual responses presented in matrices and prob: the individual probabilities.
dframe is a data frame with columns

col.resp the column group response
row.resp the row group response
x the covariate
sqn the array number
coln the column group number
rown the row group number
retest the results of individual retests

Author(s)

Boan Zhang

See Also

gtreg.mp for the corresponding function to fit the model.

Examples


# 5*6 and 4*5 matrix
set.seed(9128)
sa1a<-sim.mp(beta.par=c(-7,0.1), rown=c(5,4), coln=c(6,5),
 sens=0.95, spec=0.95)
sa1<-sa1a$dframe


[Package binGroup version 1.0-4 Index]