Creates a set of plots for an object of class cond.
# S3 method for cond
plot(x = stop("nothing to plot"), from = x.axis[1], to = x.axis[n],
which = NULL, alpha = 0.05, add.leg = TRUE, loc.leg = FALSE,
add.labs = TRUE, cex = 0.7, cex.lab = 1, cex.axis = 1,
cex.main = 1, lwd1 = 1, lwd2 = 2, lty1 = "solid",
lty2 = "dashed", col1 = "black", col2 = "blue", tck = 0.02,
las = 1, adj = 0.5, lab = c(15, 15, 5), …)a cond object. This is assumed to be the result returned
by the cond.glm function.
starting value for the x-axis range. The default value has been
set by cond.glm.
ending value for the x-axis range. The default value has been set
by cond.glm.
which plot should be printed. Admissible values are 2 to
8 corresponding to the choices in the menu below.
the level used to read off confidence intervals; default is 5%.
if TRUE, a legend is added to each plot; default is
TRUE.
if TRUE, position of the legend can be located by hand;
default is FALSE.
if TRUE, labels are added; default is TRUE.
character expansions relative to the standard size of the device
to be used for printing text, labels, axes and main title. See
par for details.
line width used to compare different curves in the same plot;
default is lwd2 = 2 for higher order solutions and
lwd1 = 1 for first order solutions.
line type used to compare different curves in the same plot;
default is lty2 = "dashed" for the Wald statistic and
lty1 = "solid" for the remaining first- and higher order
statistics.
colors used to compare different curves in the same plot; default
is col2 = "blue" for higher order solutions, and
col1 = "black" for the remaining first order statistics.
further graphical parameters. See par for
details.
optional graphical parameters; see par for
details.
A plot is created on the current graphics device.
The current device is cleared. When add.leg = TRUE, a legend
is added to each plot, and if loc.leg = TRUE, it can be set
by the user. All screens are closed, but not cleared, on
termination of the function.
Several plots are produced for an object of class cond. A
menu lists all the plots that can be produced. They may be one or
all of the following ones:
Make a plot selection (or 0 to exit)1:plot: All 2:plot: Profile and modified profile log likelihoods 3:plot: Profile and modified profile likelihood ratios 4:plot: Profile and modified likelihood roots 5:plot: Modified and continuity corrected likelihood roots 6:plot: Lugannani-Rice approximations 7:plot: Confidence intervals 8:plot: Diagnostics based on INF/NP decomposition
Selection:
If no nuisance parameters are presented, a subset of the above pictures is produced. More details on the implementation are given in Brazzale (1999, 2000).
This function is a method for the generic function plot()
for class cond. It can be invoked by calling plot
or directly plot.cond for an object of the appropriate class.
Brazzale, A. R. (1999) Approximate conditional inference for logistic and loglinear models. J. Comput. Graph. Statist., 8, 1999, 653--661.
Brazzale, A. R. (2000) Practical Small-Sample Parametric Inference, Ph.D. Thesis N. 2230, Department of Mathematics, Swiss Federal Institute of Technology Lausanne.
# NOT RUN {
## Crying Babies Data
data(babies)
babies.glm <- glm(formula = cbind(r1, r2) ~ day + lull - 1,
family = binomial, data = babies)
babies.cond <- cond(object = babies.glm, offset = lullyes)
# }
# NOT RUN {
plot(babies.cond)
# }
# NOT RUN {
## Urine Data
data(urine)
urine.glm <- glm(r ~ I(gravity * 100) + ph + osmo + conduct + urea + calc,
family = binomial, data = urine)
urine.cond <- cond(urine.glm, I(gravity * 100))
plot(urine.cond, which=4)
# }
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