[R-sig-ME] cross validation on discrete time survival analysis

[shahla ebrahimi]

   Dear Mr./Ms.Greetings
I would be very grateful if you could let me know how to do cross validation when estimating a discrete time survival analysis in R.
ID TIME EVENT  x1       x2    x3      x4       x5
1   1   0   1.281   0.023   0.875   1.216   0.061
1   2   0   1.270   0.006   0.821   1.005   -0.014
1   3   0   1.053   -0.059  0.922   0.729   0.020
1   4   0   1.113   -0.015  0.859   0.810   0.076
1   5   1   1.220   -0.059  0.887   0.484   0.010
2   1   0   1.062   0.107   0.815   0.836   0.200
2   2   0   1.056   0.082   0.879   0.687   0.143
2   3   0   0.971   0.076   0.907   0.810   0.166
2   4   0   1.059   0.130   0.818   0.876   0.234
2   5   0   1.125   0.148   0.759   1.080   0.276
2   6   0   1.600   0.262   0.546   1.313   0.369
2   7   0   1.576   0.262   0.564   1.156   0.349
2   8   0   1.544   0.241   0.591   1.077   0.326
2   9   0   1.722   0.215   0.552   0.841   0.293
2   10  0   1.723   0.209   0.534   0.787   0.293
2   11  0   1.631   0.186   0.548   0.728   0.274
2   12  0   2.172   0.319   0.441   0.947   0.427
3   1   0   0.874   -0.035  0.794   0.610   -0.003
3   2   1   0.825   -0.142  0.952   0.573   -0.019 require(lme4) model <- glmer(EVENT ~ TIME + (1+TIME|ID)+x1+x2+x3+x4+x5, data=df, family=binomial) p <- as.numeric(predict(model, type="response")>0.5) acc=mean(p==df$EVENT)
Thanks in advance.Best regards,   

   

   

   
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