ltable (version 2.0.2)

[,powerClass-method: Method for Function [

Description

Method for function [ with
signature(x = "powerClass")

Usage

# S4 method for powerClass
[(x, i, j, drop)

Methods

signature(x = "powerClass", i = "character", j = "integer", drop = "logical")

Method for function [ for object of S4 class powerClass.

Arguments

x

the name of powerClass object.

i

the name of the slot of the object

j

picks up j-th element of the list in slot with name &i.

drop

not used

Details

Method provides access to slots of powerClass object. Its structure delivered in powerClass-class index. Access to particular vectors of lists supplied with $ operator. For example, log-linear reg.coefficients estimates of smallest size data accessible by obj["estim", 1]$betas, errors can be obtained by analogue: obj["estim", 1]$errors. Power values extraction slightly differs: obj["power11", 1]&power extracts power values vector for 1st effect given 11th (largest) sample size. By analogue we get vector of z-scores for second effect given smallest sample size by obj["power1", 2]&z. See powerClass-class index.

Examples

require(ltable)
require(ltable)
data(tdata, package="ltable")
## For better illustration You should increase draw and burnin pars
pres<-MCPower(Counts~smoker +contraceptive +tromb +  
contraceptive*tromb, scale_max=1.5, effect="contraceptive*tromb", 
data=tdata, draw=1000, burnin=300)
# get call
pres["cal"]
# get effect contrasts names
pres["effectsname"]
# get Jacobian reciprocal condition number in smallest sample
pres["estim",1]$Jacobian_rcnumber
# get chisq/n in smallest sample
pres["estim",1]$chi_sq
# get LogLikelihood
pres["estim",1]$LL
# get initial deviation between observed and expected counts
pres["estim",1]$dev0
# get final deviation between observed and expected counts
pres["estim",1]$dev