Set up

library(pmplots)
library(dplyr)

Example data

There is are example data sets embedded in pmplots

Rationale

For most applications, pmplots does not reshape your data frame; it works with what you pass in. However, for some applications, it is convenient to have a diagnostic plot that is faceted by a categorical variable in the data set. This vignette demostrates the faceted plots that are available. This faceting support is for a focused set of plots only. Users should generally either create facets own or use the split_plot function for other applications.

Plots

wrap_res_time

Enter a vector of column names (or col_label) for the y argument

wrap_res_time(data, y = c("CWRESI", "WRES"))
## `geom_smooth()` using formula 'y ~ x'

wrap_eta_cont

Here, enter a vector for the x argument

wrap_eta_cont(
  id,
  x = c("WT//WT (kg)", "BMI//BMI (kg/m2)", "ALB//ALB (g/dL)"),
  y = "ETA1//ETA-CL",
  scales="free_x",
  use_labels=TRUE
)
## `geom_smooth()` using formula 'y ~ x'

In this example, we enter labels along with column names and request that the labels be used for the shingle.

We can facet on x or y

wrap_eta_cont(
  id,
  x = "WT",
  y = c("ETA1", "ETA2", "ETA3"),
  scales="free_x"
)
## `geom_smooth()` using formula 'y ~ x'

wrap_hist

Create a histogram with vector x column names

wrap_hist(data, x = c("CWRESI", "WRES"))
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

DV vs pred and DV vs ipred

wrap_dv_preds(data, yname = "MRG1557")
## `geom_smooth()` using formula 'y ~ x'