visualize the PERCH etiology regression with a continuous covariate
visualize the PERCH etiology regression with a continuous covariate
This function is specifically designed for PERCH data, e.g., (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.)
DIR_NPLCM: File path to the folder containing posterior samples
stratum_bool: integer; for this function, indicates which strata to plot
bugs.dat: The posterior samples (loaded into the environment to save time) -> default is NULL
slice: integer; specifies which slice of bronze-standard data to visualize; Default to 1.
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).
Returns
A figure of etiology regression curves and some marginal positive rate assessment of model fit; See example for the legends.