prepare_data: Data pre-processing for analysis with stochastic process...

In izhbannikov/spm: Stochastic Process Model for Analysis of Longitudinal and Time-to-Event Outcomes

Data pre-processing for analysis with stochastic process model methodology.

Description

Data pre-processing for analysis with stochastic process model methodology.

Usage

prepare_data(
  x,
  col.id = NA,
  col.status = NA,
  col.age = NA,
  col.age.event = NA,
  covariates = NA,
  interval = 1,
  verbose = FALSE
)

Arguments

x	A path to the file with table of follow-up oservations (longitudinal table). File formats: csv, sas7bdat
col.id	A name of column containing subject ID. This ID should be the same in both x (longitudinal) and y (vital statistics) tables. None: if col.id not provided, the first column of the x and first column of the y will be used by default.
col.status	A name of the column containing status variable (0/1, which is an indicator of death/censoring). Note: if not provided - then the column #2 from the y (vital statistics) dataset will be used.
col.age	A name of age column (also called 't1'). This column represents a time (age) of measurement. If not provided then the 3rd column from the longitudinal dataset (x) will be used.
col.age.event	A name of 'event' column. The event column indicates a time when the even occured (e.g. system failure). Note: if not provided then the 3rd column from the y (vital statistics) dataset will be used.
covariates	A list of covariates (physiological variables). If covariates not provided, then all columns from longitudinal table having index > 3 will be used as covariates.
interval	A number of breaks between observations for data for discrete model. This interval must be integer and should be equal or greater than 1. Default = 1 unit of time.
verbose	A verbosing output indicator. Default=FALSE.

Value

A list of two elements: first element contains a preprocessed data for continuous model, with arbitrary intervals between observations and second element contains a prepocessed data table for a discrete model (with constant intervals between observations).

Examples

## Not run:  
library(stpm) 
data <- prepare_data(x=system.file("extdata","longdat.csv",package="stpm"))
head(data[[1]])
head(data[[2]])

## End(Not run)

izhbannikov/spm documentation built on Sept. 10, 2022, 12:15 p.m.