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Hello R-users, I have been trying to fit what I think is a simple mixed-effects model using lmer (from lme4), but I've run into some difficulty that I have not been able to resolve using the existing archives or Pinheiro and Bates (2000). I am measuring populations (of birds) which change with time at a number of different sites. These sites are grouped into regions. Sites are not measured

Greetings, I have a data set look like this: > print(MyResult) 2 5 9 10 11 13 mean 6.108394 3.272211e+01 3.951703e+02 2.086217e+03 79.838867 2.592272e+04 median 1.288889 2.743511e+00 4.061491e+00 4.943710e+01 -2.821667 -3.040625e+00 var 2885.350595 2.343144e+05 1.022680e+06 1.200589e+07 365179.508831

The following fit does not make sense to me, please, correct me if I have a logical error. > moddowsn Call: coxph(formula = Surv(start, stop, resp) ~ sn + matfac2, data = coxsn1, method = "efron") coef exp(coef) se(coef) z p sn2 0.0497 1.051 0.02030 2.450 1.4e-02 sn3 -0.0532 0.948 0.02038 -2.610 9.0e-03 sn4 -0.0410 0.960

Hi all, I try to represent a multiple curve graphic where the x-axis is the temperature and the different y-axes are the different X (X22,X43,X44...) some X corresponds to the same molecule (22 and 44 are for CO2 for instance) so I use the same colour for them. I wanna mix the linetype with the colour to be able to visually see the difference between X43 and X45 The best I have done up to now

Dear useRs, I am trying to fit a Cox PH model on survival data from a lung cancer dataset. I would like to include the patient staging (I-IV) as a covariate. For this I use the following function: coxph(Surv(time,status) ~ stage) The staging information is a categorical variable, and it is important to take the ordering into account (I<II<III<IV). Does the coxph function handle