observed: Specify observed dataset and variables for VPC

In tidyvpc: VPC Percentiles and Prediction Intervals

Specify observed dataset and variables for VPC

Description

The observed function is the first function in the vpc piping chain and is used for specifying observed data and variables for VPC. Note: Observed data must not contain missing DV and may require filtering MDV == 0 before generating VPC.

Usage

observed(o, ...)

## S3 method for class 'data.frame'
observed(
  o,
  x,
  yobs,
  pred = NULL,
  blq = NULL,
  lloq = -Inf,
  alq = NULL,
  uloq = Inf,
  ...
)

Arguments

o	A data.frame of observation data.
...	Other arguments.
x	Numeric x-variable, typically named TIME.
yobs	Numeric y-variable, typically named DV.
pred	Population prediction variable, typically named PRED.
blq	Logical variable indicating below limit of quantification.
lloq	Number or numeric variable in data indicating the lower limit of quantification.
alq	Logical variable indicating above limit of quantification .
uloq	Number or numeric variable in data indicating the upper limit of quantification.

Value

A tidyvpcobj containing both original data and observed data formatted with x and y variables as specified in function. Resulting data is of class data.frame and data.table.

See Also

simulated censoring stratify predcorrect binning binless vpcstats

Examples

obs_data <- obs_data[MDV == 0]
sim_data <- sim_data[MDV == 0]

vpc <- observed(obs_data, x=TIME, y=DV)

tidyvpc documentation built on Nov. 2, 2023, 6:26 p.m.