plot_panels function

Plot three-panel figures for nested partially-latent model results

plot_panels() visualizes the model outputs for communicating how the data inform final latent disease status (etiology). It works for singleton or combo etiologies.

plot_panels(
  DIR_NPLCM,
  slices = "all",
  bg_color = list(BrS = "lavenderblush", SS = "mistyrose", pie = "antiquewhite"),
  select_latent = NULL,
  exact = TRUE,
  SS_upperlimit = 1,
  eti_upperlimit = 1,
  silent = TRUE,
  ref_eti0 = NULL,
  is_plot = TRUE
)

Arguments

• DIR_NPLCM: File path to the folder containing posterior samples

• slices: DEFAULT is "all" - to plot all measurements; Otherwise, one can specify a list: list(MBS=c(1,3),MSS=1) means to plot the 1st and 3rd slice of BrS measurements and 1st of SS measurement.

• bg_color: A list with names "BrS", "SS", "pie" to specify background colors. The current default is list(BrS = "lavenderblush", SS = "mistyrose", pie="antiquewhite"). If no background is intended, specify as NULL or for a particular measurement, e.g., BrS = NULL.

• select_latent: a vector of character strings representing latent status. It is used for just plotting a subset of latent status. For example, you can specify select_latent = "HINF"

  to plot all latent status information relevant to "HINF".

• exact: Default is TRUE to use select_latent as exact names of causes. If you want to specify a name and plot all single or combo causes with that name, specify it to be FALSE.

• SS_upperlimit: The upper limit of horizontal bar for the silver-standard subpanel (the middle panel). The default value is .25.

• eti_upperlimit: The upper limit of horizontal bar for the etiology posterior subpanel (the rightmost panel). The default value is .4

• silent: Default is TRUE to not print any warning messages; FALSE otherwise.

• ref_eti0: reference quantiles and means; a list: pEti_ref_q, pEti_ref_mean_ord

• is_plot: default to TRUE for plotting only; set to FALSE if to get summary.

Returns

A figure with two or three columns (if is_plot=TRUE); otherwise, it provide posterior summaries of Etiology information to used by print.summary.nplcm.no_reg()

Details

Missing data for BrS or SS are dropped when calculating observed measurement positive rates

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_pie_panel(), plot_subwt_regression()