[R] problem concernig Survsplit, package survival

Thanks for bringing this issue in the book's description of survSplit() to my attention. It seems the change to the behavior of survSplit() was introduced in survival version 2.39-2. Up to (including) version 2.38-3, no formula was required if arguments 'end' and 'event' were specified. A

Re: [R] Linear relative rate / excess relative risk models

(stanFit) stanFit -Original Message- From: Wollschlaeger, Daniel Sent: Thursday, January 9, 2014 10:44 AM To: David Winsemius Cc: r-help@r-project.org Subject: RE: AW: [R] Linear relative rate / excess relative risk models Thanks for your suggestions! Here are links to simulated data

Re: [R] Linear relative rate / excess relative risk models

event and offset pyears. Many thanks, D -Original Message- From: David Winsemius [mailto:dwinsem...@comcast.net] Sent: Thursday, January 09, 2014 4:33 AM To: Wollschlaeger, Daniel Cc: r-help@r-project.org Subject: Re: AW: [R] Linear relative rate / excess relative risk models

[R] Linear relative rate / excess relative risk models

My question is how I can fit linear relative rate models (= excess relative risk models, ERR) using R. In radiation epidemiology, ERR models are used to analyze dose-response relationships for event rate data and have the following form [1]: lambda = lambda0(z, alpha) * (1 + ERR(x, beta)) *

Re: [R] Linear relative rate / excess relative risk models

Von: David Winsemius [dwinsem...@comcast.net] Gesendet: Mittwoch, 8. Januar 2014 19:06 An: Wollschlaeger, Daniel Cc: r-help@r-project.org Betreff: Re: [R] Linear relative rate / excess relative risk models I would fit a Poisson model to the dose-response data with offsets