anova.intRvals: Compares model fits of 'intRvals' objects

In adokter/droprate: Analysis of Time-Ordered Event Data with Missed Observations

Compares model fits of intRvals objects

Description

Compare model fits of intRvals objects estimated on the same data. If one object is provided, the results of a deviance test against a model without a missed event probability 'p' is reported. If two objects are provided, the results of a deviance test between the model fits of the two objects is given.

Usage

## S3 method for class 'intRvals'
anova(
  object,
  y = NULL,
  conf.level = 0.95,
  digits = max(3L, getOption("digits") - 3L),
  ...
)

Arguments

object	an object of class intRvals, usually a result of a call to estinterval
y	an (optional) object of class intRvals, usually a result of a call to estinterval
conf.level	confidence level for the deviance test
digits	the number of digits for printing to screen
...	other arguments to be passed to low level functions

Value

A list of class "anova.intRvals" with the best model (1 or 2), deviance statistic and test results

best.model

the index of the best model (1 is first argument, 2 is second)

deviance

the deviance between the two tested models

p.value

p-value for the deviance (likelihood-ratio) test

conf.level

assumed confidence level for the test

model1.call

call that generated model 1

model2.call

call that generated model 2

AIC

numeric 2-vector containg the AIC value for model 1 (first element) and model 2 (second element)

loglik

numeric 2-vector containg the log-likelihood value for model 1 (first element) and model 2 (second element)

Examples

data(goosedrop)
model1=estinterval(goosedrop$interval,fun="gamma")
# visually inspect model1 fit:
plot(model1)
# The observed distribution has intervals near zero.
# We allow a small random baseline to reduce the effect
# of intervals near zero on the fit result.
model2=estinterval(goosedrop$interval,fun="gamma",fpp.method='auto')
# model2 performs better than model1:
anova(model1,model2)

adokter/droprate documentation built on May 6, 2022, 2:44 a.m.