As you may be aware I am calculating transition probabilities using Prof Crowther slides using this website :
Ref: Slide 49 https://www.stata.com/meeting/italy1...8_Crowther.pdf
-Right now my -predictms- isn't working as you know from the previous post, until I wait for an answer from this forum. However, just thinking of my prospective analysis.
If one has a dataset of all ages from 20 - 80 and would like to generate a cost-effectiveness study to compare both treatments if the slides here are giving a reference value of 45.
How can I create a cost-effectiveness picture of the overall picture of the study population ?
A. Should I just pick the average age of the people in my study eg if the average age is 50 I would replace at1(age50)
B. Or should I omit by -at1(age45) with -standardise-
(Assuming -predictms- works with standardise which I can not test right now as it's not working for me)
Ref: Slide 49 https://www.stata.com/meeting/italy1...8_Crowther.pdf
Code:
clear all use http://fmwww.bc.edu/repec/bocode/m/multistate_example,clear msset, id(pid) states(rfi osi) times(rf os) covariates(age) mat tmat = r(transmatrix) //Declare survival data stset _stop, enter(_start) failure(_status=1) scale(12) qui stpm2 age sz2 sz3 nodes hormon pr_1 if _trans1==1, scale(h) df(3) tvc(sz2 sz3 pr_1) dftvc(1) estimates store m1 qui streg age sz2 sz3 nodes hormon pr_1 if _trans2==1, distribution(weibull) . estimates store m2 qui stpm2 age sz2 sz3 nodes hormon pr_1 if _trans3==1, scale(h) df(3) tvc(pr_1) dftvc(1) nolog estimates store m3 predictms , transmat(tmat) at1(age 45) timevar(temptime) graph models(m1 m2 m3)
-Right now my -predictms- isn't working as you know from the previous post, until I wait for an answer from this forum. However, just thinking of my prospective analysis.
If one has a dataset of all ages from 20 - 80 and would like to generate a cost-effectiveness study to compare both treatments if the slides here are giving a reference value of 45.
How can I create a cost-effectiveness picture of the overall picture of the study population ?
A. Should I just pick the average age of the people in my study eg if the average age is 50 I would replace at1(age50)
B. Or should I omit by -at1(age45) with -standardise-
Code:
predictms , transmat(tmat) standardise timevar(temptime) graph models(m1 m2 m3)
(Assuming -predictms- works with standardise which I can not test right now as it's not working for me)
