I have cohort data where status (0,10 is my outcome and treatment (trt) is my predictor that declines over time:
| trt | celltype | time | status | karno | age |
| 1 | squamous | 72 | 1 | 60 | 69 |
| 1 | squamous | 411 | 1 | 70 | 64 |
| 1 | squamous | 228 | 1 | 60 | 38 |
| 1 | squamous | 126 | 1 | 60 | 63 |
| 1 | squamous | 118 | 1 | 70 | 65 |
| 1 | squamous | 10 | 1 | 20 | 49 |
| 1 | squamous | 82 | 1 | 40 | 69 |
| 1 | squamous | 110 | 1 | 80 | 68 |
| 1 | squamous | 314 | 1 | 50 | 43 |
| 1 | squamous | 100 | 0 | 70 | 70 |
| 1 | squamous | 42 | 1 | 60 | 81 |
| 1 | squamous | 8 | 1 | 40 | 63 |
| 1 | squamous | 144 | 1 | 30 | 63 |
| 1 | squamous | 25 | 0 | 80 | 52 |
| 1 | squamous | 11 | 1 | 70 | 48 |
| 1 | smallcell | 30 | 1 | 60 | 61 |
| 1 | smallcell | 384 | 1 | 60 | 42 |
| 1 | smallcell | 4 | 1 | 40 | 35 |
| 1 | smallcell | 54 | 1 | 80 | 63 |
| 1 | smallcell | 13 | 1 | 60 | 56 |
| 1 | smallcell | 123 | 0 | 40 | 55 |
| 1 | smallcell | 97 | 0 | 60 | 67 |
| 1 | smallcell | 153 | 1 | 60 | 63 |
| 1 | smallcell | 59 | 1 | 30 | 65 |
| 1 | smallcell | 117 | 1 | 80 | 46 |
| 1 | smallcell | 16 | 1 | 30 | 53 |
I am trying to estimate a constant value for this decline.
I am using the following code
gen mu=0.01
stset time, failure(status)
forvalues i=1/10 {
replace mu =0.01*`i'
stcox karno, tvc(trt) texp(exp(-mu*_t))
}
But then to use optimization to find the value of "mu" where maximum likelihood is the least and I am stuck at this point. Mata does not seem to be able to factor existing stata commands like stcox.
Any guidance will be of great help
