nestedMethods: Methods for '"nestedLogit"' and Related Objects

In nestedLogit: Nested Dichotomy Logistic Regression Models

Methods for "nestedLogit" and Related Objects

Description

Various methods for processing "nestedLogit" and related objects. Most of these are the standard methods for a model-fitting function.

coef, vcov

Return the coefficients and their variance-covariance matrix respectively.

update

Re-fit a "nestedLogit" model with a change in any of the formula, dichotomies, data, subset, or contrasts, arguments.

predict, fitted

Computes predicted values from a fitted "nestedLogit" model.

confint

Compute point-wise confidence limits for predicted response-category probabilities or logits.

glance

Construct a single row summaries for the dichotomies "nestedLogit" model.

tidy

Summarizes the terms in "nestedLogit" model.

Usage

## S3 method for class 'nestedLogit'
print(x, ...)

## S3 method for class 'nestedLogit'
summary(object, ...)

## S3 method for class 'summary.nestedLogit'
print(x, ...)

## S3 method for class 'dichotomies'
print(x, ...)

## S3 method for class 'nestedLogit'
predict(object, newdata, model = c("nested", "dichotomies"), ...)

## S3 method for class 'predictNestedLogit'
print(x, n = min(10L, nrow(x$p)), ...)

## S3 method for class 'predictNestedLogit'
confint(
  object,
  parm = c("prob", "logit"),
  level = 0.95,
  conf.limits.logit = TRUE,
  ...
)

## S3 method for class 'predictDichotomies'
print(x, n = 10L, ...)

## S3 method for class 'nestedLogit'
fitted(object, model = c("nested", "dichotomies"), ...)

## S3 method for class 'nestedLogit'
coef(object, as.matrix = TRUE, ...)

## S3 method for class 'nestedLogit'
vcov(object, as.matrix = FALSE, ...)

## S3 method for class 'nestedLogit'
update(object, formula, dichotomies, data, subset, contrasts, ...)

## S3 method for class 'dichotomies'
as.matrix(x, ...)

## S3 method for class 'dichotomies'
as.character(x, ...)

## S3 method for class 'continuationDichotomies'
as.matrix(x, ...)

as.dichotomies(x, ...)

## S3 method for class 'matrix'
as.dichotomies(x, ...)

Arguments

x, object	in most cases, an object of class "nestedLogit".
...	arguments to be passed down.
newdata	For the predict method, a data frame containing combinations of values of the predictors at which fitted probabilities (or other quantities) are to be computed.
model	For the predict and fitted methods, either "nested" (the default), in which case fitted probabilities under the nested logit model are returned, or "dichotomies", in which case predict.glm is invoked for each binary logit model fit to the nested dichotomies and a named list of the results is returned.
n	For the print method of predict.nestedLogit or predictDichotomies, an integer or "all" to control how many rows are printed for each of the probabilities of response categories, corresponding logits and their standard errors.
parm	For the confint method, one of "prob" or "logit", indicating whether to generate confidence intervals for probabilities or logits of the responses.
level	Confidence level for the confint method
conf.limits.logit	When parm = "prob" ?????
as.matrix	if TRUE (the default for coef) return coefficients as a matrix with one column for each nested dichotomy, or coefficient covariances as a matrix with one row and column for each combination of dichotomies and coefficients; if FALSE (the default for vcov), return a list of coefficients or coefficient covariances with one element for each dichotomy.
formula	optional updated model formula.
dichotomies	optional updated dichotomies object.
data	optional updated data argument
subset	optional updated subset argument.
contrasts	optional updated contrasts argument.

Details

The predict method provides predicted values for two representations of the model. model = "nested" gives the fitted probabilities for each of the response categories. model = "dichotomies" gives the fitted log odds for each binary logit models in the dichotomies.

Value

• The coef and vcov methods return either matrices or lists of regression coefficients and their covariances, respectively.

• The update method returns an object of class "nestedLogit" (see nestedLogit) derived from the original nested-logit model.

• The predict and fitted methods return an object of class "predictNested" or "predictDichotomies", which contain the predicted probabilities, predicted logits, and other information, such as standard errors of predicted values, and, if supplied, the newdata on which predictions are based.

• The summary method returns an object of class "summary.nestedLogit", which is a list of summaries of the glm objects that comprise the nested-dichotomies model; the object is normally printed.

• The methods for as.matrix, as.character, and as.dichotomies coerce various objects to matrices, character vectors, and dichotomies objects.

• The various print methods invisibly return their x arguments.

Author(s)

John Fox and Michael Friendly

See Also

nestedLogit, plot.nestedLogit, glance.nestedLogit, tidy.nestedLogit

Examples

# define continuation dichotomies for level of education
cont.dichots <- continuationLogits(c("l.t.highschool",
                                     "highschool",
                                     "college",
                                     "graduate"))

# Show dichotomies in various forms
print(cont.dichots)
as.matrix(cont.dichots)
as.character(cont.dichots)

# fit a nested model for the GSS data examining education degree in relation to parent & year
m <- nestedLogit(degree ~ parentdeg + year,
                 cont.dichots,
                 data=GSS)

coef(m)                             # coefficient estimates
sqrt(diag(vcov(m, as.matrix=TRUE))) # standard errors
print(m)
summary(m)

# broom methods
broom::glance(m)
broom::tidy(m)

# predicted probabilities and ploting
predict(m) # fitted probabilities for first few cases;

new <- expand.grid(parentdeg=c("l.t.highschool",  "highschool",
                               "college", "graduate"),
                   year=c(1972, 2016))
fit <- predict(m, newdata=new)
cbind(new, fit) # fitted probabilities at specific values of predictors

# predicted logits for dichotomies
predictions <- predict(m, newdata=new, model="dichotomies")
predictions

nestedLogit documentation built on July 9, 2023, 6:35 p.m.