LinearRateChangeDrop: Create a Dropout Mechanism with drop out rate which changes...

In dejaVu: Multiple Imputation for Recurrent Events

Description

Creates an MAR DropoutMechanism object where subject i has piecewise exponential dropout rate where the rate changes by a constant amount after each event, specifically after j events the subject has rate Rij = Cj*exp(Xij) where Cj=C+j*D for constants C, D and Xij is a standard normal variable with mean 0 and standard deviation sigma

Usage

LinearRateChangeDrop(starting.rate, rate.change, var = 0)

Arguments

starting.rate	C, see description section.
rate.change	D, see description section. Note if D<0, Cj could be negative for large j, this is not possible and the rate remains constant if the next change would set Cj<=0
var	sigma^2, see description section

Value

A DropoutMechanism object

See Also

DropoutMechanism.object

Examples

LinearRateChangeDrop(starting.rate=0.0025,rate.change=0.0005)
LinearRateChangeDrop(starting.rate=0.0025,rate.change=-0.00001,var=1)

dejaVu documentation built on April 27, 2021, 5:07 p.m.