confint.sanon: Confidence Intervals for Model Parameters

In sanon: Stratified Analysis with Nonparametric Covariable Adjustment

Description

Computes confidence intervals for one or more parameters in a fitted model.

Usage

## S3 method for class 'sanon'
confint(object, parm = NULL, level = 0.95, ...)

## S3 method for class 'confint.sanon'
print(x, ...)

Arguments

object, x	an object of class "sanon", usually, a result of a call to sanon
parm	a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered.
level	the confidence level required.
...	further arguments passed to or from other methods.

Details

Confidence intervals for adjusted parameters in the weighted least squares are computed based on an asymptotic normal.

Value

ci	A matrix (or vector) with columns giving Mann-Whiteney estimates and their lower and upper confidence limits for each parameter with estimates. The interval will be labelled as Lower for (1 - level)/2 limit and Upper for 1 - (1 - level)/2 limit (by default 0.025 and 0.975).
level	Confidence level
advarnames	Adjust variable names in the weighted least squares method

Examples

##### Example 3.1 Randomized Clinical Trial of Chronic Pain #####
data(cpain)
out1 = sanon(response ~ grp(treat, ref="placebo") + strt(center) + strt(diagnosis), data=cpain)
confint(out1)

##### Example 3.2 Randomized Clinical Trial of Respiratory Disorder #####
data(resp)
P = rbind(rep(0, 4), diag(4), rep(0, 4))
out23 = sanon(cbind(baseline, visit1, visit2, visit3, visit4) ~ grp(treatment, ref="P")
 + strt(center) + strt(sex) + covar(age), data=resp, P=P)
# each four visits
confint(out23)

sanon documentation built on July 8, 2020, 6:54 p.m.