sim_cont: Simulate continuous outcome data from a cross-over trial
In mjg211/xover: Design and analysis of cross-over clinical trials

Description Usage Arguments Details Value References See Also

Facilitates the simulation of continuous outcome data from a cross-over trial, for a given cross-over design.

1
2
3

sim_cont(sequences, n = 1, replicates = 1000, intercept, period,
  treatment, carryover, subject, sigma_b = 1, sigma_e = 1,
  random = T, seed = Sys.time(), summary = T)

`sequences`	An object of class `xover_seq`, describing the cross-over design for which data will be simulated.
`n`	Either a single `numeric` integer describing the number of subjects assigned to all of the sequences, or a `numeric` vector of integers having length equal to the number of sequences implied by `sequences`, with the elements describing the number of subject assigned to each of the sequences.
`replicates`	A single `numeric` integer describing the number of replicate datasets to generate.
`intercept`	A single `numeric` describing the intercept of the GLMM.
`period`	A `numeric` vector of length equal to one less than the number of periods implied by `sequences`, describing the values of each of the period effects.
`treatment`	A `numeric` vector of length equal to one less than the number of treatments implied by `sequences`, describing the values of each of the treatment effects.
`carryover`	A `numeric` vector of length equal to one less than the number of treatments implied by `sequences`, describing the values of each of the carryover effects.
`subject`	A `numeric` vector of length equal to one less than the number of subjects implied by `n` and `sequences`, describing the values of each of the subject effects.
`sigma_b`	A single strictly positive `numeric` describing the value of the between subject standard deviation.
`sigma_e`	A single strictly positive `numeric` describing the value of the residual standard deviation.
`random`	A `logical` variable indicating whether to treat the subject effects as random or fixed.
`seed`	A random number seed, to be passed to `set.seed`.
`summary`	A `logical` variable indicating whether a summary of the function's progress should be printed to the console. Defaults to `T`.

sim_bin() supports the simulation of continuous outcome data from a cross-over trial. Precisely, a cross-over design of class xover_seq is provided (see sequences). Then, the values of treatment, period, and several other input arguments determines the distribution of the simulated data. See the package vignette for further dettails.

A list or class xover_sim containing in particular a list sim_data which holds the simulated data.

Jones B, Kenward MG (2014) Design and Analysis of Cross-Over Trials. Chapman and Hall: London, 3rd Edition.

as_xover_seq for converting designs to class xover_seq.

mjg211/xover documentation built on Oct. 16, 2019, 10:46 a.m.