[R] predict 'expected' with eha package

[Mike Harwood]

I am unsure what is being returned, and what is supposed to be
returned, when using 'predict' with "type='expected'" for an aftreg
survival model.  The code below first generates a weibull  model, then
uses predict to create a vector of the linear predictors, then
attempts to create the 'expected' vector, which is empty.  The final
two steps in the code generate a lognormal model with the same data,
and the same empty 'expected' vector.

My expectation had been that 'expected' would generate the same
transformed dependent variable output as predict with a survreg model
using type='response'.  Since my 'real' data is left-truncated and
right-censored I cannot use survreg, and I wanted to investigate the
output from eha.

Thanks in advance!

Mike

> data(mort)
> aftreg(Surv(enter, exit, event) ~ ses, data = mort)
Call:
aftreg(formula = Surv(enter, exit, event) ~ ses, data = mort)

Covariate          W.mean      Coef Exp(Coef)  se(Coef)    Wald p
ses
           lower    0.416     0         1           (reference)
           upper    0.584    -0.348     0.706     0.089     0.000

log(scale)                    3.603    36.698     0.065     0.000
log(shape)                    0.331     1.392     0.058     0.000

Events                    276
Total time at risk         17038
Max. log. likelihood      -1391.3
LR test statistic         16.1
Degrees of freedom        1
Overall p-value           5.91578e-05
> m1 <- aftreg(Surv(enter, exit, event) ~ ses, data = mort)
> head(predict(m1, type='lp')) ## produces output
        1         2         3         4         5         6
-0.347853  0.000000 -0.347853  0.000000  0.000000  0.000000
> head(predict(m1, type='expected')) ## is this correct?
numeric(0)
> m2 <- aftreg(Surv(enter, exit, event) ~ ses, dist='lognormal', data = mort)
> head(predict(m2, type='expected')) ## is this correct?
numeric(0)


from eha (the survival and rms packages are not an option for my
'real' question, since I have left-truncated right-censored data