ci.lin {Epi} | R Documentation |
For a given model object the function computes a linear function of the parameters and the corresponding standard errors, p-values and confidence intervals.
ci.lin( obj, ctr.mat = NULL, subset = NULL, diffs = FALSE, fnam = !diffs, vcov = FALSE, alpha = 0.05, Exp = FALSE )
obj |
A model object (of class lm , glm , lme ,
coxph or polr ).
|
ctr.mat |
Contrast matrix to be multiplied to the parameter vector, i.e. the desired linear function of the parameters. |
subset |
The subset of the parameters to be used. If given as a
character vector, the elements are in turn matched against the
parameter names (using grep ) to find the subset. Repeat
parameters may result from using a character vector. This is
considered a facility. |
diffs |
If TRUE, all differences between parameters
in the subset are computed. ctr.mat is ignored. If obj
inherits from lm , and subset is given as a string
subset is used to search among the factors in the model and
differences of all factor levels for the first match are shown.
If subset does not match any of the factors in the model, all
pairwise differences between parameters matching are returned. |
fnam |
Should the common part of the parameter names be included
with the annotation of contrasts? Ignored if diffs==T . If a
sting is supplied this will be prefixed to the labels. |
vcov |
Should the covariance matrix of the set of parameters be
returned? If this is set, Exp is ignored. |
alpha |
Significance level for the confidence intervals. |
Exp |
If TRUE columns 5:6 are replaced with exp( columns 1,5,6 ). |
A matrix with number of rows and rownames as ctr.mat
. The
columns are Estimate, Std.Err, z, P, 2.5% and 97.5%.
If vcov=TRUE
a list with components est
, the desired
functional of the parameters and vcov
, the variance
covariance matrix of this, is returned but not printed.
If Exp==TRUE
the confidence intervals for the parameters are
replaced with three columns: exp(estimate,c.i.).
Bendix Carstensen, http://www.pubhealth.ku.dk/~bxc
# Bogus data: f <- factor( sample( letters[1:5], 200, replace=TRUE ) ) g <- factor( sample( letters[1:3], 200, replace=TRUE ) ) x <- rnorm( 200 ) y <- 7 + as.integer( f ) * 3 + 2 * x + 1.7 * rnorm( 200 ) # Fit a simple model: mm <- lm( y ~ x + f + g ) ci.lin( mm ) ci.lin( mm, subset=3:6, diff=TRUE, fnam=FALSE ) ci.lin( mm, subset=3:6, diff=TRUE, fnam=TRUE ) ci.lin( mm, subset="f", diff=TRUE, fnam="f levels:" ) print( ci.lin( mm, subset="g", diff=TRUE, fnam="gee!:", vcov=TRUE ) ) # Use character defined subset to get ALL contrasts: ci.lin( mm, subset="f", diff=TRUE )