Summarizing Linear Logistic Models with Relaxed Assumptions (LLRA)
summary method for class "llra"
## S3 method for class 'llra' summary(object, level, ...) ## S3 method for class 'summary.llra' print(x, ...)
object |
an object of class "llra", typically result of a call to
|
x |
an object of class "summary.llra", usually, a result of a call
to |
level |
The level of confidence for the confidence intervals. Default is 0.95. |
... |
further arguments passed to or from other methods. |
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.
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. |
Thomas Rusch
The model fitting function LLRA.
##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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.