predDF: Create a new data frame for prediction

In JointAI: Joint Analysis and Imputation of Incomplete Data

Create a new data frame for prediction

Description

Build a data.frame for prediction, where one variable varies and all other variables are set to the reference value (median for continuous variables).

Usage

predDF(object, ...)

## S3 method for class 'JointAI'
predDF(object, vars, length = 100L, ...)

## S3 method for class 'formula'
predDF(object, data, vars, length = 100L, ...)

## S3 method for class 'list'
predDF(object, data, vars, length = 100L, idvar = NULL, ...)

Arguments

object	object inheriting from class 'JointAI'
...	optional specification of the values used for some (or all) of the variables given in vars
vars	name of variable that should be varying
length	number of values used in the sequence when vars is continuous
data	a data.frame containing the original data (more details below)
idvar	optional name of an ID variable

See Also

predict.JointAI, lme_imp, glm_imp, lm_imp

Examples

# fit a JointAI model
mod <- lm_imp(y ~ C1 + C2 + M2, data = wideDF, n.iter = 100)

# generate a data frame with varying "C2" and reference values for all other
# variables in the model
newDF <- predDF(mod, vars = ~ C2)

head(newDF)


newDF2 <- predDF(mod, vars = ~ C2 + M2,
                 C2 = seq(-0.5, 0.5, 0.25),
                 M2 = levels(wideDF$M2)[2:3])
newDF2

JointAI documentation built on April 27, 2023, 5:15 p.m.