constraint statement does not work for factor variables.

[ngwali]

Hi Chris,

Thanks you so much for assisting me with setting up the constraint matrix. But I have a new problem on this matrix.

sex is a covariate in my mode.
I have 8 levels in the Q-matrix, some tranisitions not allowed are 2-8, 7-1, 8-1, 8-2, 8-3.

Option 1: Sex is a factor variable coded "Female", "Male"

sex.msm <- msm(state ~ Obstime, subject = subj, data = DF,
obstype = 2,
gen.inits=init,
qmatrix = Q,
method = "BFGS",
opt.method = "optim",
covariates = ~ sex,
constraint=list(sex=c( 1, 1, 1, 1, 1, 1, 1,
-1, 2, 2, 2, 2, 2,
-1, -2, 3, 3, 3, 3, 3,
-1, -2, -3, 4, 4, 4, 4,
-1, -2, -3, -4, 5, 5, 5,
-1, -2, -3, -4, -5, 6, 6,
-2, -3, -4, -5, -6, 7,
-4, -5, -6, -7)),
control = list (fnscale=95161, trace = 2, REPORT = 1,maxit=15000, reltol=1e-8))
Error in msm.check.constraint(constraint, mm) :
Covariate "sex" in constraint statement not in model.
In addition: Warning message:
In if (gen.inits) { :
the condition has length > 1 and only the first element will be used

**Option 2 : Sex is a numeric variable having values 0, 1. Sex is not Not a factor No errors whatsoever.

DF$sex <-as.numeric(DF$sex)
DF$sex[DF$sex==1]=0
DF$sex[DF$sex==2]=1

sex.msm <- msm(state ~ Obstime, subject = subj, data = DF,
obstype = 2,
gen.inits=init,
qmatrix = Q,
method = "BFGS",
opt.method = "optim",
covariates = ~ sex,
constraint=list(sex=c( 1, 1, 1, 1, 1, 1, 1,
-1, 2, 2, 2, 2, 2,
-1, -2, 3, 3, 3, 3, 3,
-1, -2, -3, 4, 4, 4, 4,
-1, -2, -3, -4, 5, 5, 5,
-1, -2, -3, -4, -5, 6, 6,
-2, -3, -4, -5, -6, 7,
-4, -5, -6, -7)),
control = list (fnscale=95161, trace = 2, REPORT = 1,maxit=15000, reltol=1e-8))
initial value 1.000000
final value 0.999298
converged
Used 33 function and 31 gradient evaluations

NB: Option 2 does work with no errors. My worries are as follows:

I have a factor variable called DMT with foour levels "DMT cat 1", "DMT cat 2", "DMT cat 3", and "DMT cat 4", where "DMT cat 4" is the reference level. This becomes an issue converting it to a numeric variables with values 1,2,3, 4, because the you cannot get separate hazards for level 1, 2, and 3 when using the constraint statement. However, using DMT as factor with 4 levels without the constraint statement produces hazards for 3 levels.

Can you sove this problem for me please? would be very much happy.

Thanks.

[chjackson]

See help(msm) section constraint:

          For categorical covariates, defined as factors, specify
          constraints as follows:
          'list(..., covnameVALUE1 = c(...), covnameVALUE2 = c(...),
          ...)'
          where 'covname' is the name of the factor, and 'VALUE1',
          'VALUE2', ... are the labels of the factor levels (usually
          excluding the baseline, if using the default contrasts).

There was actually a bug in the error handling here - there was supposed to be a warning message like the following, but this was not being triggered. I've fixed that in the development version.

Error in msm.check.constraint(constraint, mm) : 
  Covariate "sex" in constraint statement not in model.
	For factor covariates, specify constraints using covnameCOVVALUE = c(...)

[ngwali]

That works now.

Many thanks for this.