spss='elliotreg.sav';

model:'A. 1-class: standard ordinal logistic regression'  regression     1 /
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=0  nseedboot=0
  nrand=10
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
attr time ordinal ;
attr sex ordinal ;
attr marijuan ordinal ;
classind time sex;

end;
model:'B. 2-class: intercept class specific'  regression     2 /
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=577201  nseedboot=0
  nrand=0
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
attr time ordinal ;
attr sex ordinal ;
attr marijuan ordinal ;
classind time sex;

end;
model:'C. 3-class: intercept class specific'  regression     3 /
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=1817008  nseedboot=0
  nrand=0
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
attr time ordinal ;
attr sex ordinal ;
attr marijuan ordinal ;
classind time sex;

end;
model:'D. 4-class: intercept class specific'  regression     4 /
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=1589168  nseedboot=0
  nrand=0
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
attr time ordinal ;
attr sex ordinal ;
attr marijuan ordinal ;
classind time sex;

end;
model:'E1. 2-class: intercept+slope class specific'  regression     2 /
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=238346  nseedboot=0
  nrand=0
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
attr time ordinal ;
attr sex ordinal ;
attr marijuan ordinal ;
classind sex;

end;
model:'E2. 3-class: intercept+slope class specific'  regression     3 /
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=2352047  nseedboot=0
  nrand=0
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
attr time ordinal ;
attr sex ordinal ;
attr marijuan ordinal ;
classind sex;

end;
model:'F. 4-class: intercept+slope class specific'  regression     4 /
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=1391679  nseedboot=0
  nrand=0
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
attr time ordinal ;
attr sex ordinal ;
attr marijuan ordinal ;
classind sex;

end;
model:'G.1-class: ordinal logistic regression with random intercept'  regression     1 /
  cfn=1  cfnde=10  cfcsp=0
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=2617360  nseedboot=0
  nrand=0
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
cfactor 1 <- marijuan;
attr time ordinal ;
attr sex ordinal ;
attr marijuan ordinal ;
classind sex;

end;
model:'H. 2-class: intercept+slope class specific + random intercept'  regression     2 /
  cfn=1  cfnde=10  cfcsp=0
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=551774  nseedboot=0
  nrand=0
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
cfactor 1 <- marijuan;
attr time ordinal ;
attr sex ordinal ;
attr marijuan ordinal ;
classind sex;

end;
model:'I. 3-class: intercept+slope class specific + random intercept'  regression     3 /
  cfn=1  cfnde=10  cfcsp=0
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=301896  nseedboot=0
  nrand=0
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
cfactor 1 <- marijuan;
attr time ordinal ;
attr sex ordinal ;
attr marijuan ordinal ;
classind sex;

end;
model:'J. 4-class: intercept+slope class specific + random intercept'  regression     4 /
  cfn=1  cfnde=10  cfcsp=0
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=1218534  nseedboot=0
  nrand=0
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
cfactor 1 <- marijuan;
attr time ordinal ;
attr sex ordinal ;
attr marijuan ordinal ;
classind sex;

end;
model:'K. as H with sex as covariate  2'  regression     2 /
  cfn=1  cfnde=10  cfcsp=0
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=551774  nseedboot=0
  nrand=0
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
covariate sexcov;
cfactor 1 <- marijuan sexcov;
attr time ordinal ;
attr sex ordinal ;
attr sexcov ordinal ;
attr marijuan ordinal ;
classind sex;

end;
model:'L. as H with no time effect in class 2'  regression     2 /
  cfn=1  cfnde=10  cfcsp=0
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=310548  nseedboot=0
  nrand=0
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
cfactor 1 <- marijuan;
attr time ordinal ;
attr sex ordinal ;
attr marijuan ordinal ;
classind sex;
restrict time 1 0;

end;
model:'K. as H with time dummies in class 1 and no time effect in class 2'  regression     2 /
  cfn=1  cfnde=10  cfcsp=0
  toler=1e-008  tolem=0.01  tolran=1e-005  bayes=1  bayess2=1  bayeslat=1
  bayespoi=1
  iterem=250  iternr=50  itersv=50
  iterboot=500
  nseed=2722578  nseedboot=0
  nrand=0
  usemiss=No
  sewald=yes  dummy=no
 outsect=0x1c17
;
casewgt freq;
dependent marijuan;
replicate id;
predictor time sex;
cfactor 1 <- marijuan;
attr time nominal ;
attr sex ordinal ;
attr marijuan ordinal ;
classind sex;
restrict time 1 0;

end;