simulate_ss: Simulate Silver-Standard (SS) Data

In zhenkewu/baker: "Nested Partially Latent Class Models"

Simulate Silver-Standard (SS) Data

Description

Simulate Silver-Standard (SS) Data

Usage

simulate_ss(set_parameter, latent_samples)

Arguments

set_parameter

True model parameters in an npLCM specification: cause_list a vector of disease class names among cases (since the causes could be multi-agent (e.g., multiple pathogens may cause an individual case's pneumonia), so its length could be longer than the total number of unique causative agents) etiology a vector of proportions that sum to 100 percent pathogen_BrS a vector of putative causative agents' names measured in bronze-standard (BrS) data. This function simulates only one slice defined by ⁠specimen``test``pathogen⁠ pathogen_SS a vector of pathogen names measured in silver-standard (SS) data. meas_nm a list of ⁠specimen``test⁠ names e.g., list(MBS = c("NPPCR"),MSS="BCX") for nasopharyngeal (NP) specimen tested by polymerase chain reaction (PCR) - NPPCR and blood (B) tested by culture (Cx) - BCX Lambda controls' subclass weights \nu_1, \nu_2, \ldots, \nu_K a vector of K probabilities that sum to 1. Eta a matrix of dimension length(cause_list) by K; each row represents a disease class (among cases); the values in that row are subclass weights \eta_1, \eta_2, \ldots, \eta_K for that disease class, so needs to sum to one. In Wu et al. 2016 (JRSS-C), the subclass weights are the same across disease classes across rows. But when simulating data, one can specify rows with distinct subclass weights - it is a matter whether we can recover these parameters (possible when some cases' true disease classes are observed) PsiBS/PsiSS False positive rates for Bronze-Standard data and for Silver-Standard data. For example, the rows of PsiBS correspond to the dimension of the particular slice of BrS measures, e.g., 10 for 10 causative agents measured by NPPCR; the columns correspond to K subclasses; generically, the dimension is J by K PsiSS is supposed to be a vector of all zeros (perfect specificity in silver-standard measures). ThetaBS/ThetaSS True positive rates \Theta for Bronze-Standard data and for Silver-Standard data. Dimension is J by K (can contain NA if the total number of causative agents measured by BrS or SS exceeds the measured causative agents in SS. For example, in PERCH study, nasopharyngeal polymerase chain reaction (NPPCR; bronze-standard) may target 30 distinct pathogens, but blood culture (BCX; silver-standard) may only target a subset of the 30, so we have to specify NA in ThetaSSfor those pathogens not targeted by BCX). Nu the number of control subjects Nd the number of case subjects

latent_samples

simulated latent status for all the subjects, for use in simulating SS measurements.

Value

a data frame with first column being case-control status (case at top) and columns of silver-standard measurements

See Also

Other internal simulation functions: simulate_brs(), simulate_latent()

zhenkewu/baker documentation built on May 6, 2024, 11:19 p.m.