Zelig (version 3.5.1)

plot.ci: Plotting Vertical confidence Intervals

Description

The plot.ci command generates vertical confidence intervals for linear or generalized linear univariate response models.

Usage

plot.ci(x, CI = 95, qi = "ev", main = "", ylab = NULL, xlab = NULL,
        xlim = NULL, ylim = NULL, col = c("red", "blue"), ...)

Arguments

x

stored output from sim. The x$x and optional x$x1 values used to generate the sim output object must have more than one observation.

CI

the selected confidence interval. Defaults to 95 percent.

qi

the selected quantity of interest. Defaults to expected values.

main

a title for the plot.

ylab

label for the y-axis.

xlab

label for the x-axis.

xlim

limits on the x-axis.

ylim

limits on the y-axis.

col

a vector of at most two colors for plotting the expected value given by x and the alternative set of expected values given by x1 in sim. If the quantity of interest selected is not the expected value, or

...

Additional parameters passed to plot.

Value

• For all univariate response models, plot.ci() returns vertical confidence intervals over a specified range of one explanatory variable. You may save this plot using the commands described in the Zelig manual (http://gking.harvard.edu/zelig).

See Also

The full Zelig manual is available at http://gking.harvard.edu/zelig, and users may also wish to see plot, lines.

Examples

data(turnout)
z.out <- zelig(vote ~ race + educate + age + I(age^2) + income,
               model = "logit", data = turnout)
age.range <- 18:95
x.low <- setx(z.out, educate = 12, age = age.range)
x.high <- setx(z.out, educate = 16, age = age.range)
s.out <- sim(z.out, x = x.low, x1 = x.high)
plot.ci(s.out, xlab = "Age in Years",
        ylab = "Predicted Probability of Voting",
        main = "Effect of Education and Age on Voting Behavior")
legend(45, 0.52, legend = c("College Education (16 years)",
       "High School Education (12 years)"), col = c("blue","red"), 
       lty = c("solid"))

## adding lines connecting point estimates
lines(age.range, apply(s.out$qi$ev, 2, mean))
lines(age.range, apply(s.out$qi$fd+s.out$qi$ev, 2, mean))