get.ts.ng.mc.df: Get two-sample normal-gamma MC-based data.frame

In GNGTools: Tools for Go/No-Go Decision-Making Framework

Get two-sample normal-gamma MC-based data.frame

Description

Get two-sample normal-gamma MC-based data.frame

Usage

get.ts.ng.mc.df(
  mu.0.c = 0,
  n.0.c = 10,
  alpha.0.c = 0.25 * 4,
  beta.0.c = 1 * 4,
  xbar.c = seq(-3, 3, length.out = 20),
  s.c = 3,
  n.c = 25,
  group.c = "Control",
  mu.0.t = 0,
  n.0.t = 10,
  alpha.0.t = 0.25 * 4,
  beta.0.t = 1 * 4,
  xbar.t = seq(0, 6, length.out = 20),
  s.t = 2,
  n.t = 25,
  group.t = "Treatment",
  Delta.tv = 1.75,
  Delta.lrv = 1.5,
  tau.tv = 0.1,
  tau.lrv = 0.8,
  tau.ng = 0,
  n.MC = 1000,
  seed = 1234,
  expand = TRUE
)

Arguments

mu.0.c	prior mean for control group
n.0.c	prior effective sample size for control group
alpha.0.c	prior alpha parameter for control group
beta.0.c	prior beta parameter for control group
xbar.c	sample mean for control group
s.c	sample sd for control group
n.c	sample size for control group
group.c	group label for control group
mu.0.t	prior mean for treatment group
n.0.t	prior effective sample size for treatment group
alpha.0.t	prior alpha parameter for treatment group
beta.0.t	prior beta parameter for treatment group
xbar.t	sample mean for treatment group
s.t	sample sd for treatment group
n.t	sample size for treatment group
group.t	group label for treatment group
Delta.tv	TPP Target Value aka Base TPP
Delta.lrv	TPP Lower Reference Value aka Min TPP
tau.tv	threshold associated with Base TPP
tau.lrv	threshold associated with Min TPP
tau.ng	threshold associated with No-Go
n.MC	number of MC sampling
seed	random seed
expand	logical; if true expand.grid is employed; else data.frame is employed. Former provides all combinations

Value

A data.frame is returned

Examples

my.ts.ng.mc.df <- get.ts.ng.mc.df()
my.ts.ng.mc.df

GNGTools documentation built on Dec. 16, 2022, 5:09 p.m.