Thanks for the advice, I will use next years. Till know i´ve just got data
for 3 independent months and one of the months it´s the joining for all the
summer because of the small sample size, so, I suppose, I can't use it in
the way you say.
-
Mario Garrido Escudero
PhD student
Dpto. de
Hello,
I´m starting with my PhD and I have to stop because i got a little knowledge
in R and statistics.
I´ve got a model of this kind:
binary response variable: prevalence of infection (0/1)
3 categorical independent variables: sex, month and name of the area
I was trying with a full model
On Jan 12, 2011, at 12:51 PM, gaiarrido wrote:
Hello,
I´m starting with my PhD and I have to stop because i got a little
knowledge
in R and statistics.
I´ve got a model of this kind:
binary response variable: prevalence of infection (0/1)
3 categorical independent variables: sex, month and
Hi,
That is basically correct. You can specify the link as logit (see my
example), but that is the default so you do not strictly need to in
this case. II would encourage you to keep your variables
(prevalencia, edad, sexo, mes) stored in a data frame, in which case
you would add the data =
Thanks very much both.
I´m starting playing with it, i was a little afaid because it was part of my
job, but now i've found it very funny.
Josh, I've got just data for 3 representatives months, and it's not a priori
rejectable that could be differences in the ratio of changes along the
months
... But I would think that month should be treated as a cyclical
quantity, not as a factor with 12 independent levels, e.g. by
transforming month to sin( 2*pi*monthNumber/12) . This assumes 1
year periodicity, which might not be right, of course. Time series
methods could obviously be relevant
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