Plotting Nested Logit Models

A plot method for "nestedLogit" objects produced by the nestedLogit function. Fitted probabilities under the model, or the corresponding logits are plotted for each level of the polytomous response variable, with one of the explanatory variables on the horizontal axis and other explanatory variables fixed to particular values. By default, a 95% pointwise confidence envelope is added to the plot.

Usage

# S3 method for class 'nestedLogit'
plot(
  x,
  x.var,
  others,
  n.x.values = 100L,
  scale = c("prob", "logit"),
  xlab = x.var,
  ylab = NULL,
  main,
  cex.main = 1,
  digits.main = getOption("digits") - 2L,
  font.main = 1L,
  pch = 1L:length(response.levels),
  lwd = 3,
  lty = 1L:length(response.levels),
  col = (scales::hue_pal())(length(response.levels)),
  legend = TRUE,
  legend.inset = 0.01,
  legend.location = "topleft",
  legend.bty = "n",
  conf.level = 0.95,
  conf.alpha = 0.25,
  label = FALSE,
  label.x = "max",
  label.cex = 1.25,
  label.col = col,
  ...
)

Arguments

x: an object of "nestedLogit" produced by nestedLogit.
x.var: quoted name of the variable to appear on the x-axis; if omitted, the first predictor in the model is used.
others: a named list of values for the other variables in the model, that is, other than x.var; if any other predictor is omitted, it is set to an arbitrary value—the mean for a numeric predictor or the first level or value of a factor, character, or logical predictor; only one value may be specified for each variable in others.
n.x.values: the number of evenly spaced values of x.var at which to evaluate fitted probabilities to be plotted (default 100).
scale: character string; "prob" (the default) plots fitted probabilities on the y-axis; "logit" plots fitted log odds (logits), i.e., \(\log(p/(1-p))\).
xlab: label for the x-axis (defaults to the value of x.var).
ylab: label for the y-axis (defaults to "Fitted Probability" when scale = "prob" and "Fitted Log Odds" when scale = "logit").
main: main title for the graph (if missing, constructed from the variables and values in others).
cex.main: size of main title (see par).
digits.main: number of digits to retain when rounding values for the main title.
font.main: font for main title (see par).
pch: plotting characters (see par).
lwd: line width (see par).
lty: line types (see par).
col: line colors for the response levels (see par).
legend: if TRUE (the default), add a legend for the response levels to the graph. Ignored when label = TRUE.
legend.inset: default 0.01 (see legend).
legend.location: position of the legend (default "topleft", see legend).
legend.bty: the type of box to be drawn around the legend. The allowed values are "o" (the default) and "n".
conf.level: the level for pointwise confidence envelopes around the predicted values; the default is 0.95. If NULL, the confidence envelopes are suppressed.
conf.alpha: the opacity of the confidence envelopes; the default is 0.3.
label: if TRUE, label the curves directly instead of using a legend. Default is FALSE.
label.x: where to place the label for each curve. Either a single string, "min" or "max" (applied to all curves), or a character vector of length equal to the number of response categories with each element being "min" or "max", e.g. label.x = c("min", "max", "max"). "min" places the label at the left end of the curve; "max" (the default) places it at the right end.
label.cex: character expansion factor for direct labels; default 1.25.
label.col: colors for direct labels; defaults to col, so labels match their curves. Supply a vector of length equal to the number of response categories to use different colors for the labels.
...: arguments to be passed to matplot.

Value

NULL Used for its side-effect of producing a plot

Author

John Fox, Michael Friendly

Examples

data("Womenlf", package = "carData")
m <- nestedLogit(partic ~ hincome + children,
                 logits(work=dichotomy("not.work", c("parttime", "fulltime")),
                        full=dichotomy("parttime", "fulltime")),
                        data=Womenlf)
plot(m, legend.location="top")
#> Note: hincome will be used for the horizontal axis
#> Note: missing predictor children set to its first level, 'absent'


op <- par(mfcol=c(1, 2), mar=c(4, 4, 3, 1) + 0.1)
plot(m, "hincome", list(children="absent"),
     xlab="Husband's Income", legend=FALSE)
plot(m, "hincome", list(children="present"),
     xlab="Husband's Income")

par(op)

# Plot on the logit (log-odds) scale
plot(m, "hincome", list(children="absent"), scale = "logit",
     xlab = "Husband's Income")


# Gators example: direct curve labels instead of a legend
data("gators", package = "nestedLogit")
gators.nested <- nestedLogit(food ~ length,
  logits(d1 = dichotomy("Other", c("Fish", "Invertebrates")),
         d2 = dichotomy("Fish", "Invertebrates")),
  data = gators)

# All labels at the right end (default)
plot(gators.nested, x.var = "length", label = TRUE,
     xlab = "Alligator length (m)")


# Mixed placement: Other and Invertebrates labeled at left, Fish at right
# (food levels are: "Other", "Fish", "Invertebrates")
plot(gators.nested, x.var = "length", label = TRUE,
     label.x = c("min", "max", "min"),
     xlab = "Alligator length (m)")

Usage

Arguments

Value

See also

Author

Examples