I did something similar a while ago using -nlcom- on an estimated
ordered ologit with -gllamm-. An example of how I did it is presented
below using auto.dta.
// Michael
clear
sysuse auto
// Create level 2 ID
gen make2 = substr(make, 1, index(make, " "))
egen pick =tag(make2)
gen id=_n if pick
sort make2 id
replace id = id[_n-1] if id == .
// Make turn>40 a dichotomous predictor variable
gen turn40 = turn > 40
// estimate gllamm model on rep78 with turn40 as predictor
gllamm rep78 turn40 , i(id) link(ologit) fam(bin) adapt
// Use local macros to temporary hold your input values
local pv1 = 1 // predictor value 1
local pv2 = 0 // predictor value 2
local cut = 11 // Choose cut point i.e. which level of the dependent
variable you want to predict
// calculate log of the ratio of the two probabilities predicted from
pv1/pv2
nlcom ln( (exp(`pv1' * [rep78]turn40 - [_cut`cut']_cons) / ///
(1 + exp(`pv1' * [rep78]turn40 - [_cut`cut']_cons))) / ///
(exp(`pv2' * [rep78]turn40 - [_cut`cut']_cons) / ///
(1 + exp(`pv2' * [rep78]turn40 - [_cut`cut']_cons))))
// Store the results from -nlcom-
matrix b = r(b)
matrix V = r(V)
// Values needs to be exponentiated to describe RRR
di "RRR: " exp(b[1,1])
di "Lower 95% CI " exp(b[1,1] - sqrt(V[1,1])*1.96)
di "Upper 95% CI " exp(b[1,1] + sqrt(V[1,1])*1.96)
On 2005-03-23, at 20:49, INAGAMI,SANAE wrote:
I have looked at the gllamm manual. I just don't know how to write the
commands.
I want to know the probability of each ordered outcome conditional on a
categorical predictor variable being 1.
Then with the same command, I want to change the predictor variable to
0.
Then I would like to set up a relative risk of outcomes by creating a
ratio of the probabilities (1 vs 0).
Then I would like to come up with confidence intervals for those
ratios.
I can do this in ordered logistic stata, but I can't do it with glamm
because I think I set up the syntax incorrectly.
Thanks.
Sanae
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------------------------------------------------
Michael Ingre , PhD student & Research Associate
Department of Psychology, Stockholm University &
National Institute for Psychosocial Medicine IPM
Box 230, 171 77 Stockholm, Sweden
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