plot_subwt_regression: visualize the subclass weight regression with a continuous...

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

visualize the subclass weight regression with a continuous covariate

Description

visualize the subclass weight regression with a continuous covariate

Usage

plot_subwt_regression(
  DIR_NPLCM,
  stratum_bool,
  case = 0,
  slice = 1,
  truth = NULL,
  RES_NPLCM = NULL
)

Arguments

DIR_NPLCM	File path to the folder containing posterior samples
stratum_bool	a vector of TRUE/FALSE with TRUE indicating the rows of subjects to include
case	1 for plotting cases, 0 for plotting controls; default to 0.
slice	integer; specifies which slice of bronze-standard data to visualize; Default to 1.
truth	a list of truths computed from true parameters in simulations; elements: Eti, FPR, PR_case,TPR; All default to NULL in real data analyses. Currently only works for one slice of bronze-standard measurements (in a non-nested model). truth_subwt matrix of # of rows = # of subjects, # columns: number of true subclasses
RES_NPLCM	pre-read res_nplcm; default to NULL.

Value

A figure of subclass regression curves

See Also

Other visualization functions: plot.nplcm(), plot_BrS_panel(), plot_SS_panel(), plot_check_common_pattern(), plot_check_pairwise_SLORD(), plot_etiology_regression(), plot_etiology_strat(), plot_panels(), plot_pie_panel()

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