Wrapped / Faceted Plots

Set up

library(pmplots)

## Error in get(paste0(generic, ".", class), envir = get_method_env()) : 
##   object 'type_sum.accel' not found

library(dplyr)

Example data

There is are example data sets embedded in pmplots

data <- pmplots_data_obs()
id <- pmplots_data_id()

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 demonstrates 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'

Kyle Baron

2024-12-19