summary.llra: Summarizing Linear Logistic Models with Relaxed Assumptions...

In eRm: Extended Rasch Modeling

Summarizing Linear Logistic Models with Relaxed Assumptions (LLRA)

Description

summary method for class "llra"

Usage

## S3 method for class 'llra'
summary(object, level, ...)

## S3 method for class 'summary.llra'
print(x, ...)

Arguments

object	an object of class "llra", typically result of a call to LLRA.
x	an object of class "summary.llra", usually, a result of a call to summary.llra.
level	The level of confidence for the confidence intervals. Default is 0.95.
...	further arguments passed to or from other methods.

Details

Objects of class "summary.llra" contain all parameters of interest plus the confidence intervals.

print.summary.llra rounds the values to 3 digits and displays them nicely.

Value

The function summary.lllra computes and returns a list of summary statistics of the fitted LLRA given in object, reusing the components (list elements) call, etapar, iter, loglik, model, npar and se.etapar from its argument, plus

ci	The upper and lower confidence interval borders.

Author(s)

Thomas Rusch

See Also

The model fitting function LLRA.

Examples

##Example 6 from Hatzinger & Rusch (2009)
groups <- c(rep("TG",30),rep("CG",30))
llra1 <- LLRA(llradat3,mpoints=2,groups=groups)
summary(llra1)

## Not run: 
##An LLRA with 2 treatment groups and 1 baseline group, 5 items and 4
##time points. Item 1 is dichotomous, all others have 3, 4, 5, 6
##categories respectively.
ex2 <- LLRA(llraDat2[1:20],mpoints=4,llraDat2[21])
sumEx2 <- summary(ex2, level=0.95)

#print a summary
sumEx2

#get confidence intervals
sumEx2$ci
## End(Not run)

eRm documentation built on May 29, 2024, 2:12 a.m.