simstudy (version 0.7.0)

genSpline: Generate spline curves

Description

Generate spline curves

Usage

genSpline(
  dt,
  newvar,
  predictor,
  theta,
  knots = c(0.25, 0.5, 0.75),
  degree = 3,
  newrange = NULL,
  noise.var = 0
)

Value

A modified data.table with an added column named newvar.

Arguments

dt

data.table that will be modified

newvar

Name of new variable to be created

predictor

Name of field in old data.table that is predicting new value

theta

A vector or matrix of values between 0 and 1. Each column of the matrix represents the weights/coefficients that will be applied to the basis functions determined by the knots and degree. Each column of theta represents a separate spline curve.

knots

A vector of values between 0 and 1, specifying quantile cut-points for splines. Defaults to c(0.25, 0.50, 0.75).

degree

Integer specifying polynomial degree of curvature.

newrange

Range of the spline function , specified as a string with two values separated by a semi-colon. The first value represents the minimum, and the second value represents the maximum. Defaults to NULL, which sets the range to be between 0 and 1.

noise.var

Add to normally distributed noise to observation - where mean is value of spline curve.

Examples

ddef <- defData(varname = "age", formula = "0;1", dist = "uniform")

theta1 <- c(0.1, 0.8, 0.6, 0.4, 0.6, 0.9, 0.9)
knots <- c(0.25, 0.5, 0.75)

viewSplines(knots = knots, theta = theta1, degree = 3)

set.seed(234)
dt <- genData(1000, ddef)

dt <- genSpline(
  dt = dt, newvar = "weight",
  predictor = "age", theta = theta1,
  knots = knots, degree = 3,
  noise.var = .025
)

dt