surveillance (version 1.12.1)

twinstim_step: Stepwise Model Selection by AIC

Description

stepComponent is a wrapper around step to select a "twinstim" component's model based on an information criterion in a stepwise algorithm.

There are also stand-alone single-step methods of add1 and drop1.

Usage

stepComponent(object, component = c("endemic", "epidemic"),
              scope = list(upper = object$formula[[component]]),
              direction = "both", trace = 2, verbose = FALSE, ...)

## S3 method for class 'twinstim': add1(object, scope, component = c("endemic", "epidemic"), trace = 2, ...) ## S3 method for class 'twinstim': drop1(object, scope, component = c("endemic", "epidemic"), trace = 2, ...)

Arguments

object
an object of class "twinstim".
component
one of "endemic" or "epidemic" (partially matched), determining the model component where the algorithm should proceed.
scope,direction,trace
see step and add1, respectively.
verbose
...
further arguments passed to step, add1.default, or drop1.default, respectively.

Value

See Also

step, add1, drop1

Examples

Run this code
data("imdepi")
data("imdepifit")

## simple baseline model
m0 <- update(imdepifit, epidemic=~1, siaf=NULL, start=c("e.(Intercept)"=-17))

## AIC-based step-wise backward selection of the endemic component
m0_step <- stepComponent(m0, "endemic", scope=list(lower=~I(start/365-3.5)))
## nothing is dropped from the model

m0_step$anova <- NULL
stopifnot(identical(m0, m0_step))

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