ctIntervalise: Converts absolute times to intervals for wide format ctsem...

In ctsem: Continuous Time Structural Equation Modelling

Converts absolute times to intervals for wide format ctsem panel data

Description

Converts absolute times to intervals for wide format ctsem panel data

Usage

ctIntervalise(
  datawide,
  Tpoints,
  n.manifest,
  n.TDpred = 0,
  n.TIpred = 0,
  imputedefs = F,
  manifestNames = "auto",
  TDpredNames = "auto",
  TIpredNames = "auto",
  digits = 5,
  mininterval = 0.001,
  individualRelativeTime = TRUE,
  startoffset = 0
)

Arguments

datawide	Wide format data, containing absolute time measurements, to convert to interval time scale. See ctLongToWide to easily convert long format data.
Tpoints	Maximum number of discrete time points (waves of data, or measurement occasions) for an individual in the input data structure.
n.manifest	number of manifest variables per time point in the data.
n.TDpred	number of time dependent predictors in the data structure.
n.TIpred	number of time independent predictors in the data structure.
imputedefs	if TRUE, impute time intervals based on the measurement occasion (i.e. column) they are in, if FALSE (default), set related observations to NA. FALSE is recommended unless you are certain that the imputed value (mean of the relevant time column) is appropriate. Noise and bias in estimates will result if wrongly set to TRUE.
manifestNames	vector of character strings giving variable names of manifest indicator variables (without _Tx suffix for measurement occasion).
TDpredNames	vector of character strings giving variable names of time dependent predictor variables (without _Tx suffix for measurement occasion).
TIpredNames	vector of character strings giving variable names of time independent predictor variables.
digits	How many digits to round to for interval calculations.
mininterval	set to lower than any possible observed measurement interval, but above 0 - this is used for filling NA values where necessary and has no impact on estimates when set in the correct range. (If all observed intervals are greater than 1, mininterval=1 may be a good choice)
individualRelativeTime	if TRUE (default), the first measurement for each individual is assumed to be taken at time 0, and all other times are adjusted accordingly. If FALSE, new columns for an initial wave are created, consisting only of observations which occurred at the earliest observation time of the entire sample.
startoffset	if 0 (default) uses earliest observation as start time. If greater than 0, all first observations are NA, with distance of startoffset to first recorded observation.

Details

Time column must be numeric!

Examples

wideexample <- ctLongToWide(datalong = ctstantestdat, id = "id", 
time = "time", manifestNames = c("Y1", "Y2"), 
TDpredNames = "TD1", TIpredNames = c("TI1", "TI2","TI3"))

#Then convert the absolute times to intervals, using the Tpoints reported from the prior step.
wide <- ctIntervalise(datawide = wideexample, Tpoints = 10, n.manifest = 2, 
n.TDpred = 1, n.TIpred = 3, manifestNames = c("Y1", "Y2"), 
TDpredNames = "TD1", TIpredNames = c("TI1", "TI2","TI3") )
 
print(wide)

ctsem documentation built on Sept. 11, 2024, 9:06 p.m.