calcpresdSurvdat: Prepare the data needed to calculate survivorship for...

In robschick/tangled: Creates data objects and plots for Knowlton, Schick et al. manuscript on entanglement

Prepare the data needed to calculate survivorship for presumed dead animals

Description

Goal of this is to ingest the events data frame and the output from calckdpaSurvdat() to make one list that can be used to calculate survivorship. The first element of this list will be the presumed Alive and known Dead animals. All other elements will contain the presumed dead animals. The goal of this structure was to be able to

Usage

calcpresdSurvdat(events, kdpasurvldf)

Arguments

events	a data frame of the last entanglement event for individual whales.
kdpasurvldf	a data frame output from the calckdpaSurvdat() function. These are the preparatory data for calculating survivorship

Value

survdf a many by 10 stacked data frame containing the information needed to calculate survivorship (Done in another function).

EGNo

Numerical identifier of the individual whale

deathMonth

Integer noting the death month of the animal, i.e. the median month it was estimated to die in

censored

Logical indicating whether or not the animal was censored at dcut

censMonth

Integer indicating the integer time for dcut

survTime0

Integer noting the length of time between the end of the entanglement window and the deathMonth

deathMonth0

Integer noting the maximum of survTime0

censMonth0

Integer indicating number of months between the end of the entanglement and the censoring month (censMonth)

Severity

Character describing the severity of the entanglement injury. Ordinal values include: minor, moderate, and severe

gearInj

Integer denoting our numerical representation of the entanglement injury and whether or not the injury includes gear

knownDeath

Logical indicating whether or not the animal is known to have died

Examples

## Not run: 
calcpresdSurvdat(events, kdpasurvldf)

## End(Not run)

robschick/tangled documentation built on May 9, 2022, 4:07 p.m.