On Wed, 14 Jan 2004, Spencer Graves wrote:
Yes, but glm maximizes the binomial likelihood assuming
log(p/(1-p)) is a linear model. Therefore, you don't have to transform
the 0's and 1's. There are cases where a particular combination of
potential explanatory variables will clearly
VR describes binomial GLMs with mortality out of 20 budworms.
Is it appropriate to use the same approach with mortality out of
numbers as low as 3? I feel reticent to do so with data that is not
very continuous. There are one continuous and one categorical
independent variables.
Would it be
The advisability of using glm with mortality depends not on the
size of sample groups but on the assumption of independence: Whether
you have 3 individuals per group or 30 or 1, is it plausible to assume
that all individuals represented in your data.frame have independent
chances of
On Wed, 14-Jan-2004 at 05:15PM -0800, Spencer Graves wrote:
| The advisability of using glm with mortality depends not on
| the size of sample groups but on the assumption of independence:
| Whether you have 3 individuals per group or 30 or 1, is it
I think we can assume independence.
Yes, but glm maximizes the binomial likelihood assuming
log(p/(1-p)) is a linear model. Therefore, you don't have to transform
the 0's and 1's. There are cases where a particular combination of
potential explanatory variables will clearly separate mortalities from
survivors. I don't
idea for lots of things.
V.
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Patrick Connolly
Sent: Thursday, 15 January 2004 9:28 AM
To: R-help
Subject: [R] Binomial glms with very small numbers
VR describes binomial GLMs with mortality out of 20
