Thanks a lot to everybody. Two more questions, if you
don't mind :
How anova() treats non-categorical variables, such as
severity in my case ? I was under impression that
ANOVA is defined for categorical variables only.
I read about drop1() and I understand that it performs
F-test for nested
At 01:52 PM 12/16/2003 -0800, Alexander Sirotkin \[at Yahoo\] wrote:
Thanks a lot to everybody. Two more questions, if you
don't mind :
How anova() treats non-categorical variables, such as
severity in my case ? I was under impression that
ANOVA is defined for categorical variables only.
The term
John,
What you are saying is that any conclusion I can make
from summary.aov (for instance, to answer a question
if physician is a significant variable) will not be
correct ?
--- John Fox [EMAIL PROTECTED] wrote:
Dear Spencer and Alexander,
In this case, physician is apparently a factor
On Sun, 7 Dec 2003, Alexander Sirotkin [at Yahoo] wrote:
John,
What you are saying is that any conclusion I can make
from summary.aov (for instance, to answer a question
if physician is a significant variable) will not be
correct ?
If that is your question *both* are incorrect. The
Alexander Sirotkin [at Yahoo] [EMAIL PROTECTED] writes:
John,
What you are saying is that any conclusion I can make
from summary.aov (for instance, to answer a question
if physician is a significant variable) will not be
correct ?
Summary.aov is for summarizing aov objects, so you're
I have a simple linear model (fitted with lm()) with 2
independant
variables : one categorical and one integer.
When I run summary.lm() on this model, I get a
standard linear
regression summary (in which one categorical variable
has to be
converted into many indicator variables) which looks
like
The square of a Student's t with df degrees of freedom is an F
distribution with 1 and df degrees of freedom.
hope this helps. spencer graves
Alexander Sirotkin [at Yahoo] wrote:
I have a simple linear model (fitted with lm()) with 2
independant
variables : one categorical and
Dear Spencer and Alexander,
In this case, physician is apparently a factor with three levels, so
summary.aov() gives you a sequential ANOVA, equivalent to what you'd get
from anova(). There no simple relationship between the F-statistic for
physician, which has 2 df in the numerator, and the
