plot.neLht {medflex} | R Documentation |
Confidence interval plots for linear hypotheses in natural effect models
Description
Confidence interval plots for linear hypotheses in natural effect models.
Usage
## S3 method for class 'neEffdecomp'
plot(x, level = 0.95, transf = identity, ylabels, yticks.at, ...)
## S3 method for class 'neLht'
plot(x, level = 0.95, transf = identity, ylabels, yticks.at, ...)
## S3 method for class 'neLhtBoot'
plot(
x,
level = 0.95,
ci.type = "norm",
transf = identity,
ylabels,
yticks.at,
...
)
Arguments
x |
an object of class |
level |
the confidence level required. |
transf |
transformation function to be applied internally on the (linear hypothesis) estimates and their confidence intervals (e.g. |
ylabels |
character vector containing the labels for the (linear hypothesis) estimates to be plotted on the y-axis. |
yticks.at |
numeric vector containing the y-coordinates (from 0 to 1) to draw the tick marks for the different estimates and their corresponding confidence intervals. |
... |
additional arguments. |
ci.type |
the type of bootstrap intervals required (see |
Details
This function is an adapted version of plot.glht
from the multcomp package and
yields confidence interval plots for each of the linear hypothesis parameters.
See Also
Examples
data(UPBdata)
impData <- neImpute(UPB ~ att * negaff + gender + educ + age,
family = binomial, data = UPBdata)
neMod <- neModel(UPB ~ att0 * att1 + gender + educ + age,
family = binomial, expData = impData, se = "robust")
lht <- neLht(neMod, linfct = c("att0 = 0", "att0 + att0:att1 = 0",
"att1 = 0", "att1 + att0:att1 = 0",
"att0 + att1 + att0:att1 = 0"))
## all pairs return identical output
plot(confint(lht), transf = exp)
plot(lht, transf = exp)
plot(neEffdecomp(neMod), transf = exp)
plot(neMod, transf = exp)