mlts (version 2.0.1)

create_missings: Create Missings for Approximation of Continuous Time Dynamic Models

Description

Create Missings for Approximation of Continuous Time Dynamic Models

Usage

create_missings(data, tinterval, id, time, btw_vars = NULL)

Value

A data.frame with missings imputed for use in mlts_fit.

Arguments

data

An object of class data.frame (or one that can be coerced to that class) containing data of all variables used in the model.

tinterval

The step interval for approximation for a continuous time DSEM. The smaller the step interval, the better the approximation.

id

The variable in data that identifies the person or observational unit (as character).

time

The variable in data that contains the (continuous) time (as string).

btw_vars

The names of between-level variables in the data to be added in newly created rows with NAs.

Examples

# create some data for example
data <- data.frame(
  id = rep(c(1, 2), each = 4),
  time = c(0, 3, 4, 6,
           1, 4, 5, 7)
)

# create missings to approximate continuous time process
create_missings(
  data = data, id = "id", time = "time",
  tinterval = 1 # use time interval of 1 minute
)