anova(cph(..) output

Hi,

Thank you very much for the answer.

However, I have still some misunderstandings.
from the output, can we say that plant and leaf age are significant but not
their interaction?
And the last question I promise, what would you advise me to write in the
paper to explain the different method and ackonwledge for the df?

Thank you again,
julien.

 

Frank E Harrell Jr wrote:

pompon wrote:

Hello,

I am a beginner in R and statistics, so my question may be trivial. Sorry
in
advance.
I performed a Cox proportion hazard regression with 2 categorical
variables
with cph{design}. Then an anova on the results.
the output is 

anova(cph(surv(survival, censor) ~ plant + leaf.age + plant*leaf.age,
Mpnymph)

                Wald Statistics          Response: Surv(survival,
censored) 

 Factor                                                    Chi-Square
d.f. P     
 plant  (Factor+Higher Order Factors)             96.96     12   <.0001
  All Interactions                                               10.58     
6   0.1022
 leaf.age  (Factor+Higher Order Factors)          29.11      7   0.0001
  All Interactions                                                 10.58     
6   0.1022
 plant * leaf.age  (Factor+Higher Order Factors)  10.58      6   0.1022
 TOTAL                                           106.63     13   <.0001

What do "All interaction" stand for?
The real df of for plant is 6 and 1 for leaf.age. Then, which chi square
is
one for my main factors anf their interaction.

thank you,
Julien.

Julien,

I know what you mean when you say 'real df' but that's not the whole 
story as plant has 6 more df by interacting with a single df variable. 
There is no such thing as 'the' main effect test for plant.  The 12 df 
test is unique and tests whether plant is associated with Y for any 
level of leaf.age.

You can see exactly what is being tested by using various print options 
for anova.Design, as described in the help file.  The "dots" option is 
easy on the eyes.

Frank
-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University