RMark (version 2.1.1)

adjust.value: Adjust over-dispersion scale or a result value such as effective sample size

Description

Adjust value of over-dispersion constant or another result value for a collection of models which modifies model selection criterion and estimated standard errors.

Usage

adjust.value(field="n",value,model.list)
       adjust.chat(chat=1,model.list)

Arguments

field

Character string containing name of the field; either chat or a field in model$results such as n for sample size used in AICc or QAICc

value

new value for field

model.list

marklist created by the function collect.models which has each model object and a model.table at the end. For the entire collection of models each chat is adjusted. If th

chat

Over-dispersion scale

Value

• model.list with all models given the new chat value and model.table adjusted for chat values

Details

The value of chat is stored with the model object except when there is no over-dispersion (chat=1). This function assigns a new value of chat for the collection of models specified by model.list and/or type. The value of chat is used by model.table for model selection in computing QAICc unless chat=1. It is also used in summary.mark, get.real and compute.real to adjust standard errors and confidence intervals. Note that the standard errors and confidence intervals in results$beta,results$beta.vcv results$real, results$derived and results$derived.vcv are not modified and always assume chat=1. It can also be used to modify a field in model$results such as n which is ESS (effective sample size) from MARK output that is used in AICc/QAICc calculations.

See Also

model.table, summary.mark, get.real ,compute.real

Examples

#
# The following are examples only to demonstrate selecting different
# model sets for adjusting chat and showing model selection table.
# It is not a realistic analysis.
#
# This example is excluded from testing to reduce package check time
data(dipper)
do_example=function()
{
mod1=mark(dipper)
mod2=mark(dipper,model.parameters=list(Phi=list(formula=~time)))
mod3=mark(dipper,model="POPAN",initial=1)
cjs.results=collect.models(type="CJS")
cjs.results  # show model selection results for "CJS" models
}
cjs.results=do_example()
cjs.results
# adjust chat for all models to 2
cjs.results=adjust.chat(2,cjs.results)
cjs.results