#' Hypothetical pathogens and their categories (virus or bacteria)
#'
#' This is used in simulations where the pathogen names are from the alphabet,
#' and we hope to plot etiologies grouped by virus or bacteria
#'
#' @format A matrix of two columns
#' \describe{
#' \item{pathogen}{names of the hypothetical pathogens, A-Z}
#' \item{pathogen_type}{category of the hypothetical pathogens, `B` for
#' bacterium, `V` for virus, which are randomly assigned.}
#' }
#' @usage data("pathogen_category_simulation")
#'
#'
#' @return No returned value; just loading data into the working space.
"pathogen_category_simulation"
#' pathogens and their categories in PERCH study (virus or bacteria)
#'
#' 231 rows indicating bacteria, virus, fungi, or other categories.
#'
#' @format A matrix of two columns
#' \describe{
#' \item{pathogen}{names of the pathogens}
#' \item{pathogen_type}{category of the pathogens, `B` for
#' bacterium, `V` for virus, `F` for fungus, `O` for "not categorized"}
#' }
#'
#' @return No returned value; just loading data into the working space.
#'
#' @usage data("pathogen_category_perch")
"pathogen_category_perch"
## #' Simulated dataset that is structured in the format necessary for an [nplcm()] with regression
## #'
## #' Data set for illustrating regression functionalities
## #'
## #' @format A list containing three items
## #' \describe{
## #' \item{Mobs}{BrS level measurements: N = 1,200 (half cases and half controls);
## #' one slice of BrS measurements (6 dimensional, A-F); one slice of SS measurements (2 dimensional,
## #' A and B)}
## #' \item{Y}{case-control status}
## #' \item{X}{matrix of covariates (N by 4); columns: SITE (1 and 2, each with 600 subjects),
## #' DATE (index from 1:300), std_date (standardized DATE), ENRLDATE (actual dates)}
## #' }
## #'
## #' @usage data("data_nplcm_reg")
## "data_nplcm_reg"
#' Simulated dataset that is structured in the format necessary for an [nplcm()] with regression
#'
#' Data set for illustrating regression functionalities
#'
#' @format A list containing three items
#' \describe{
#' \item{Mobs}{BrS level measurements: N = 1,200 (half cases and half controls);
#' one slice of BrS measurements (6 dimensional, A-F); one slice of SS measurements (2 dimensional,
#' A and B)}
#' \item{Y}{case-control status}
#' \item{X}{matrix of covariates (N by 4); columns: SITE (1 and 2, each with 600 subjects),
#' DATE (index from 1:300), std_date (standardized DATE), ENRLDATE (actual dates)}
#' }
#'
#' @return No returned value; just loading data into the working space.
#' @usage data("data_nplcm_reg_nest")
"data_nplcm_reg_nest"
#' Simulated dataset that is structured in the format necessary for an [nplcm()] without regression
#'
#' Data set for illustrating regression functionalities
#'
#' @format A list containing three items
#' \describe{
#' \item{Mobs}{BrS level measurements: N = 600 (half cases and half controls);
#' one slice of BrS measurements (6 dimensional, A-F); one slice of SS measurements (2 dimensional,
#' A and B)}
#' \item{Y}{case-control status}
#' }
#'
#' @return No returned value; just loading data into the working space.
#'
#' @usage data("data_nplcm_noreg")
"data_nplcm_noreg"
# NB: a few more data sets: data_nplcm_no_reg (no regression setting); this can be used in a lot of functions
# for visualization. Perhaps also need to add posterior samples as data set just as a way to
# demonstrate the plotting functionality and unit test.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.