sim_dat_ord_logistic: Simulate Longitudinal Ordinal Data with Logistic...

In CJangelo/SPR: Tools to Learn Statistical Programming in R

Description

TODO: Build in check if the correlations are too high! Where is that code? Note that the variances aren't used if passed, Requires MASS R package

Usage

sim_dat_ord_logistic(
  N = 100,
  number.groups = 2,
  number.timepoints = 4,
  reg.formula = NULL,
  Beta = 0,
  thresholds = c(-2, -1, 0, 1),
  corr = "ar1",
  cor.value = NULL,
  cond.mcar = F,
  Covariate = F
)

Arguments

reg.formula	this is a regression formula to pass to the data generation; null is formula(~ Group + Time + Time*Group),
Beta	this is the Beta for the regression equation; numeric matrix of Beta values OR a scalar value != 0 that will be the final value of the interaction parameters, default is all(Beta == 0) for Type I error simulations
thresholds	the ordinal generation uses a logistic approach, and these are the thresholds
corr	options for correlation structure c('ind', 'ar1', 'cs'), default is 'ar1'
cor.value	numeric, the first corr in ar1, the corr in cs option
cond.mcar	logical; do you want a conditional MCAR data generation
Covariate	logical; do you want a random simulated covariate?

Value

returns a dataframe containing the simulated data

CJangelo/SPR documentation built on Feb. 24, 2022, 5:02 a.m.