addMarkov: Add Markov chain

In simstudy: Simulation of Study Data

Add Markov chain

Description

Generate a Markov chain for n individuals or units by specifying a transition matrix.

Usage

addMarkov(
  dd,
  transMat,
  chainLen,
  wide = FALSE,
  id = "id",
  pername = "period",
  varname = "state",
  widePrefix = "S",
  start0lab = NULL,
  trimvalue = NULL
)

Arguments

dd	data.table with a unique identifier
transMat	Square transition matrix where the sum of each row must equal 1. The dimensions of the matrix equal the number of possible states.
chainLen	Length of each chain that will be generated for each chain; minimum chain length is 2.
wide	Logical variable (TRUE or FALSE) indicating whether the resulting data table should be returned in wide or long format. The wide format includes all elements of a chain on a single row; the long format includes each element of a chain in its own row. The default is wide = FALSE, so the long format is returned by default.
id	Character string that represents name of "id" field. Defaults to "id".
pername	Character string that represents the variable name of the chain sequence in the long format. Defaults "period",
varname	Character string that represents the variable name of the state in the long format. Defaults to "state".
widePrefix	Character string that represents the variable name prefix for the state fields in the wide format. Defaults to "S".
start0lab	Character string that represents name of the integer field containing starting state (State 0) of the chain for each individual. If it is NULL, starting state defaults to 1. Default is NULL.
trimvalue	Integer value indicating end state. If trimvalue is not NULL, all records after the first instance of state = trimvalue will be deleted.

Value

A data table with n rows if in wide format, or n by chainLen rows if in long format.

Examples

def1 <- defData(varname = "x1", formula = 0, variance = 1)
def1 <- defData(def1, varname = "x2", formula = 0, variance = 1)
def1 <- defData(def1,
  varname = "S0", formula = ".6;.3;.1",
  dist = "categorical"
)

dd <- genData(20, def1)

# Transition matrix P

P <- t(matrix(c(
  0.7, 0.2, 0.1,
  0.5, 0.3, 0.2,
  0.0, 0.7, 0.3
),
nrow = 3
))

d1 <- addMarkov(dd, P, chainLen = 3)
d2 <- addMarkov(dd, P, chainLen = 5, wide = TRUE)
d3 <- addMarkov(dd, P, chainLen = 5, wide = TRUE, start0lab = "S0")
d4 <- addMarkov(dd, P, chainLen = 5, start0lab = "S0", trimvalue = 3)

simstudy documentation built on Nov. 23, 2023, 1:06 a.m.