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make.time.factor

Make time-varying dummy variables from time-varying factor variable


Description

Create a new dataframe with time-varying dummy variables from a time-varying factor variable. The time-varying dummy variables are named appropriately to be used as a set of time dependent individual covariates in a parameter specification

Usage

make.time.factor(x, var.name, times, intercept = NULL, delete = TRUE)

Arguments

x

dataframe containing set of factor variables with names composed of var.name prefix and times suffix

var.name

prefix for variable names

times

numeric suffixes for variable names

intercept

the value of the factor variable that will be used for the intercept

delete

if TRUE, the origninal time-varying factor variables are removed from the returned dataframe

Details

An example of the var.name and times is var.name="observer", times=1:5. The code expects to find observer1,...,observer5 to be factor variables in x. If there are k unique levels (excluding ".") across the time varying factor variables, then k-1 dummy variables are created for each of the named factor variables. They are named with var.name, level[i], times[j] concatenated together where level[i] is the name of the facto level i. If there a m times then the new data set will contain m*(k-1) dummy variables. If the factor variable includes any "." values these are ignored because they are used to indicate a missing value that is paired with a missing value in the encounter history. Note that it will create each dummy variable for each factor even if a particular level is not contained within a factor (eg observers 1 to 3 used but only 1 and 2 on occasion 1).

Value

x: a dataframe containing the original data (with time-varying factor variables removed if delete=TRUE) and the time-varying dummy variables added.

Author(s)

Jeff Laake

Examples

# see example in weta

RMark

R Code for Mark Analysis

v2.2.7
GPL (>= 2)
Authors
Jeff Laake <jefflaake@gmail.com> with code contributions from Eldar Rakhimberdiev, Ben Augustine, Daniel Turek and Brett McClintock and example data and analysis from Bret Collier, Jay Rotella, David Pavlacky, Andrew Paul, Luke Eberhart- Phillips, Jake Ivan, and Connor Wood.
Initial release
2019-11-4

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