Description Usage Arguments Value Author(s) See Also Examples
This function does one replication of the simulation for the supplemental materials section of the paper from data generated with fixed censoring times and a user-specified true event probability. It returns a description of the misclassification of both the individual and group tests, the results from the appropriate PAVA, the results from the hybrid EM-PAV algorithm for grouped tests, and the number of iterations the hybrid EM-PAV algorithm takes to converge
1 | simulation.fixed(n, k, Cs, true.F, alpha, beta, t)
|
n |
number of individuals |
k |
grouping size |
Cs |
a vector of the observed censoring times |
true.F |
a vector of event probabilities at each one of the |
alpha |
Sensitivity: probability of a positive test results given that the individual is truly diseased (or that the group contains at least one person who is truly diseased). Default is 1 - no misclassification |
beta |
Specificity: probability of a negative test results given that the individual is truly not diseased (or that the group contains noone who is truly diseased). Default is 1 - no misclassification |
t |
threshold for convergence (default is 0.01) |
The same list as returned by simulation.random
desc.ind |
Table with description of the misclassification of the individual tests |
desc.group |
Table with description of the misclassification of the group tests |
num.it |
Number of iterations for the hybrid EM-PAV algorithm to converge |
ind.result |
Result from appropriate PAV algorithm ( |
group.result |
Result from hybrid EM-PAV algorithm, see function |
Lucia Petito
hybrid.em.pav
, pava.cs.mc
, gen.data.fixed
1 | simulation(100, 2, 1:10, seq(0.05, 0.5, 0.05), 0.95, 0.95, 0.01)
|
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