Hi
I have a dataset for 16 examiners who took a test on correctly diagnosing the side of asymmetry in 6 landmarks on human body in anterior and posterior direction. I am trying to see which landmark ,asymmetry and direction combinations are most accurately answered by examiners.So there are 6 landmarks, two directions (ant and posterior) and different levels of asymmetry. Not all landmarks are tested on same level of asymmetry, which means if say landmark 1 has asymmetries 4,5,6, landmark 2 might have 2, 3, 4. and similarly other landmarks. So my level of asymmetries are 3,4,5,6,7,8 used randomly for testing students at different landmarks.
Now when I tried some techniques of making the model converge from the suggestions on other posts on similar convergence issues but still have issues in convergence. Please suggest some solution.
I reconverted my examiner id variable to make it numeric and then removed from the class statement after sorting by id. I also tried removing the direction from the model statement , but still model does not converge.
Thanks a ton!!!
proc glimmix data=dat1 noitprint; class absasym direction landmark ; model Autoscore(desc) = landmark*absasym*direction / dist=binary link=logit ddfm=kr; random intercept / subject=ID gcorr solution; nloptions technique=congra maxiter=1000 gconv=1e-4; run;
I want to run some lsmeans statements but seeing issues with convergence, I could not do so yet.
I used proc freq to see how is the missingness in different categories for landmark and absasym combinations. The table from that.
Table of Landmark by absasym
Landmark
absasym
3
4
5
6
7
8
Total
ANT IC
0
0.00
0
0.00
48
6.25
16
2.08
16
2.08
16
2.08
96
12.50
ASIS
0
0.00
64
8.33
64
8.33
64
8.33
0
0.00
0
0.00
192
25.00
ITB
0
0.00
32
4.17
32
4.17
32
4.17
0
0.00
0
0.00
96
12.50
POST IC
0
0.00
0
0.00
32
4.17
16
2.08
48
6.25
0
0.00
96
12.50
PSIS
16
2.08
48
6.25
32
4.17
96
12.50
0
0.00
0
0.00
192
25.00
PT
64
8.33
32
4.17
0
0.00
0
0.00
0
0.00
0
0.00
96
12.50
Total
80
10.42
176
22.92
208
27.08
224
29.17
64
8.33
16
2.08
768
100.00
... View more
