plot_etiology_regression: visualize the etiology regression with a continuous covariate

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

visualize the etiology regression with a continuous covariate

Description

This function visualizes the etiology regression against one continuous covariate, e.g., enrollment date. (NB: dealing with NoA, multiple-pathogen causes, other continuous covariates? also there this function only plots the first slice - so generalization may be useful - give users an option to choose slice s; currently default to the first slice.)

Usage

plot_etiology_regression(
  DIR_NPLCM,
  stratum_bool,
  slice = 1,
  plot_basis = FALSE,
  truth = NULL,
  RES_NPLCM = NULL,
  do_plot = TRUE,
  do_rug = TRUE,
  return_metric = TRUE,
  plot_ma_dots = FALSE
)

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
slice	integer; specifies which slice of bronze-standard data to visualize; Default to 1.
plot_basis	TRUE for plotting basis functions; Default to FALSE
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). Eti matrix of # of rows = # of subjects, # columns: length(cause_list) for Eti FPR matrix of # of rows = # of subjects, # columns: ncol(data_nplcm$Mobs$MBS$MBS1) PR_case matrix of # of rows = # of subjects, # columns: ncol(data_nplcm$Mobs$MBS$MBS1) TPR a vector of length identical to PR_case
RES_NPLCM	pre-read res_nplcm; default to NULL.
do_plot	TRUE for plotting
do_rug	TRUE for plotting
return_metric	TRUE for showing overall mean etiology, quantiles, s.d., and if truth$Eti is supplied, coverage, bias, truth and integrated mean squared errors (IMSE).
plot_ma_dots	plot moving averages among case and controls if TRUE; Default to FALSE.

Value

A figure of etiology regression curves and some marginal positive rate assessment of model fit; See example for the legends.

References

See example figures

• A Figure using simulated data for six pathogens: https://github.com/zhenkewu/baker/blob/master/inst/figs/visualize_etiology_regression_SITE=1.pdf

• The legends for the figure above: https://github.com/zhenkewu/baker/blob/master/inst/figs/legends_visualize_etiology_regression.png

See Also

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

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