What’s New in tidyvpc 1.3.0?

Source: vignettes/tidyvpc_1_3_0.Rmd

tidyvpc 1.3.0

An overview of updates to plot() function in tidyvpc v1.3.0

Set plot output dimensions:

knitr::opts_chunk$set(fig.width=12, fig.height=8, dpi = 300)

One sided stratify() formula uses facet_wrap()

## tidyvpc is part of Certara.R!
## Follow the link below to learn more about R package development at Cerara.
## https://certara.github.io/R-Certara/
library(magrittr)
obs_data <- obs_data[MDV == 0]
sim_data <- sim_data[MDV == 0]

vpc <- observed(obs_data, x=TIME, y=DV) %>%
  simulated(sim_data, y=DV) %>%
  stratify(~ GENDER) %>%
  binless() %>%
  vpcstats()

plot(vpc)

vpc <- observed(obs_data, x=TIME, y=DV) %>%
  simulated(sim_data, y=DV) %>%
  stratify(~ GENDER + STUDY) %>%
  binning(bin = "jenks", nbins = 8) %>%
  vpcstats()

plot(vpc)

Two-sided formula uses facet_grid()

vpc <- observed(obs_data, x=TIME, y=DV) %>%
  simulated(sim_data, y=DV) %>%
  stratify(GENDER ~ STUDY) %>%
  binning(bin = "kmeans", nbins = 6) %>%
  vpcstats()

plot(vpc)

Using facet = TRUE argument

We can use facet = TRUE argument to facet continuous VPC by quantile or facet categorical VPC by predicted probability.

vpc <- observed(obs_data, x=TIME, y=DV) %>%
  simulated(sim_data, y=DV) %>%
  binless() %>%
  vpcstats()

plot(vpc, facet = TRUE, point.alpha = 0.1, point.size = 1, ribbon.alpha = 0.2)

vpc <- observed(obs_cat_data, x = agemonths, yobs = zlencat) %>%
  simulated(sim_cat_data, ysim = DV) %>%
  binless() %>% 
  vpcstats(vpc.type = "categorical")

plot(vpc, facet = TRUE, legend.position = "bottom")

Changing point size, point alpha, point shape, point stroke, and ribbon alpha

Setup categorical VPC.

vpc <- observed(obs_cat_data, x = agemonths, yobs = zlencat) %>%
  simulated(sim_cat_data, ysim = DV) %>%
  binning(bin = round(agemonths, 0)) %>%
  vpcstats(vpc.type = "categorical")

Adjust point size.

plot(vpc, point.size = 4)

Setup continuous VPC.

vpc <- observed(obs_data, x=TIME, y=DV) %>%
  simulated(sim_data, y=DV) %>%
  binless() %>%
  vpcstats()
plot(vpc, point.size = 1.5, point.stroke = 2.5, point.alpha = 0.1, ribbon.alpha = 0.05)

plot(vpc, point.size = 5, point.stroke = 0.3, point.shape = "triangle")

plot(vpc, point.size = 7, point.shape = "square-fill", point.alpha = 0.1, ribbon.alpha = 0.5)