ID | TIME_POINT | A | B | C |
1 | 1 | 5 | 10 | 10 |
1 | 2 | 25 | 25 | 25 |
1 | 3 | 50 | 50 | 25 |
2 | 1 | 50 | 25 | 25 |
2 | 2 | 25 | 75 | 75 |
2 | 3 | 25 | 50 | 50 |
3 | 1 | 25 | 50 | 50 |
3 | 2 | 50 | 95 | 50 |
3 | 3 | 50 | 50 | 75 |
4 | 1 | 5 | 25 | 5 |
4 | 2 | 10 | 10 | 25 |
4 | 3 | 5 | 10 | 90 |
5 | 1 | 75 | 95 | 25 |
5 | 2 | 25 | 5 | 10 |
5 | 3 | 50 | 90 | 10 |
6 | 1 | 75 | 95 | 25 |
6 | 2 | 5 | 5 | 5 |
6 | 3 | 5 | 5 | 5 |
7 | 1 | 25 | 50 | 50 |
7 | 2 | 10 | 5 | 5 |
7 | 3 | 10 | 5 | 5 |
8 | 1 | 75 | 95 | 25 |
8 | 2 | 75 | 95 | 25 |
8 | 3 | 75 | 95 | 25 |
9 | 1 | 25 | 50 | 50 |
9 | 2 | 5 | 5 | 5 |
9 | 3 | 5 | 5 | 5 |
10 | 1 | 25 | 10 | 25 |
10 | 2 | 50 | 10 | 25 |
10 | 3 | 5 | 5 | 25 |
11 | 1 | 10 | 10 | 5 |
11 | 2 | 10 | 5 | 10 |
11 | 3 | 10 | 10 | 25 |
12 | 1 | 25 | 50 | 10 |
12 | 2 | 5 | 25 | 10 |
12 | 3 | 5 | 25 | 5 |
13 | 1 | 5 | 50 | 75 |
13 | 2 | 5 | 25 | 50 |
13 | 3 | 10 | 25 | 50 |
14 | 1 | 5 | 50 | 25 |
14 | 2 | 5 | 50 | 25 |
14 | 3 | 75 | 75 | 50 |
15 | 1 | 5 | 50 | 5 |
15 | 2 | 50 | 5 | 25 |
15 | 3 | 50 | 5 | 25 |
16 | 1 | 90 | 50 | 50 |
16 | 2 | 90 | 50 | 50 |
16 | 3 | 95 | 75 | 25 |
17 | 1 | 90 | 50 | 50 |
17 | 2 | 75 | 25 | 75 |
17 | 3 | 75 | 50 | 75 |
18 | 1 | 90 | 50 | 95 |
18 | 2 | 50 | 25 | 95 |
18 | 3 | 90 | 50 | 50 |
19 | 1 | 90 | 50 | 50 |
19 | 2 | 50 | 5 | 75 |
19 | 3 | 25 | 10 | 75 |
20 | 1 | 25 | 50 | 50 |
20 | 2 | 25 | 50 | 50 |
20 | 3 | 50 | 50 | 75 |
21 | 1 | 95 | 75 | 95 |
21 | 2 | 95 | 75 | 95 |
21 | 3 | 50 | 25 | 25 |
22 | 1 | 75 | 95 | 95 |
22 | 2 | 95 | 75 | 95 |
22 | 3 | 75 | 50 | 95 |
23 | 1 | 95 | 75 | 50 |
23 | 2 | 75 | 50 | 75 |
23 | 3 | 90 | 25 | 75 |
24 | 1 | 25 | 50 | 5 |
24 | 2 | 25 | 50 | 5 |
24 | 3 | 5 | 25 | 5 |
25 | 1 | 25 | 50 | 5 |
25 | 2 | 25 | 50 | 5 |
25 | 3 | 25 | 5 | 10 |
26 | 1 | 25 | 50 | 5 |
26 | 2 | 25 | 10 | 25 |
26 | 3 | 25 | 10 | 25 |
27 | 1 | 75 | 10 | 10 |
27 | 2 | 95 | 25 | 95 |
27 | 3 | 95 | 50 | 95 |
28 | 1 | 50 | 50 | 10 |
28 | 2 | 10 | 50 | 10 |
28 | 3 | 10 | 50 | 10 |
29 | 1 | 75 | 10 | 25 |
29 | 2 | 25 | 25 | 5 |
29 | 3 | 5 | 5 | 5 |
30 | 1 | 75 | 10 | 25 |
30 | 2 | 75 | 90 | 50 |
30 | 3 | 50 | 75 | 75 |
31 | 1 | 75 | 10 | 25 |
31 | 2 | 90 | 25 | 75 |
31 | 3 | 90 | 25 | 5 |
32 | 1 | 75 | 10 | 25 |
32 | 2 | 25 | 25 | 25 |
32 | 3 | 25 | 10 | 50 |
33 | 1 | 75 | 10 | 25 |
33 | 2 | 75 | 95 | 95 |
33 | 3 | 75 | 95 | 95 |
34 | 1 | 75 | 95 | 95 |
34 | 2 | 75 | 95 | 95 |
34 | 3 | 5 | 5 | 10 |
35 | 1 | 50 | 75 | 10 |
35 | 2 | 75 | 95 | 95 |
35 | 3 | 75 | 95 | 95 |
36 | 1 | 10 | 75 | 5 |
36 | 2 | 5 | 10 | 75 |
36 | 3 | 5 | 10 | 75 |
37 | 1 | 5 | 10 | 75 |
37 | 2 | 25 | 10 | 10 |
37 | 3 | 5 | 5 | 25 |
38 | 1 | 5 | 10 | 75 |
38 | 2 | 5 | 10 | 90 |
38 | 3 | 5 | 10 | 75 |
39 | 1 | 50 | 75 | 90 |
39 | 2 | 5 | 10 | 75 |
39 | 3 | 5 | 10 | 75 |
40 | 1 | 75 | 75 | 50 |
40 | 2 | 10 | 10 | 10 |
40 | 3 | 10 | 10 | 10 |
41 | 1 | 10 | 10 | 10 |
41 | 2 | 10 | 10 | 10 |
41 | 3 | 10 | 10 | 10 |
42 | 1 | 10 | 10 | 10 |
42 | 2 | 10 | 10 | 10 |
42 | 3 | 10 | 10 | 10 |
43 | 1 | 5 | 25 | 5 |
43 | 2 | 10 | 10 | 10 |
43 | 3 | 10 | 10 | 10 |
44 | 1 | 90 | 50 | 95 |
44 | 2 | 10 | 10 | 10 |
44 | 3 | 10 | 10 | 10 |
45 | 1 | 75 | 50 | 75 |
45 | 2 | 95 | 75 | 95 |
45 | 3 | 95 | 75 | 95 |
46 | 1 | 95 | 75 | 95 |
49 | 1 | 75 | 50 | 25 |
49 | 2 | 95 | 75 | 95 |
49 | 3 | 95 | 75 | 95 |
50 | 1 | 10 | 10 | 5 |
50 | 2 | 10 | 10 | 5 |
50 | 3 | 10 | 10 | 5 |
51 | 1 | 10 | 10 | 5 |
51 | 2 | 10 | 10 | 5 |
51 | 3 | 10 | 10 | 5 |
52 | 1 | 5 | 10 | 5 |
52 | 2 | 25 | 50 | 50 |
52 | 3 | 25 | 50 | 50 |
53 | 1 | 25 | 50 | 50 |
53 | 2 | 25 | 50 | 50 |
53 | 3 | 25 | 50 | 50 |
54 | 1 | 5 | 50 | 25 |
54 | 2 | 25 | 90 | 75 |
54 | 3 | 25 | 90 | 75 |
55 | 1 | 50 | 75 | 75 |
55 | 2 | 25 | 90 | 75 |
55 | 3 | 25 | 90 | 75 |
56 | 1 | 25 | 90 | 75 |
56 | 2 | 25 | 90 | 75 |
56 | 3 | 25 | 90 | 75 |
57 | 1 | 5 | 50 | 5 |
57 | 2 | 5 | 50 | 5 |
57 | 3 | 5 | 50 | 5 |
58 | 1 | 5 | 50 | 5 |
58 | 2 | 5 | 50 | 5 |
58 | 3 | 5 | 50 | 5 |
59 | 1 | 95 | 50 | 75 |
59 | 2 | 25 | 90 | 50 |
59 | 3 | 25 | 90 | 50 |
60 | 1 | 25 | 90 | 50 |
60 | 2 | 25 | 90 | 50 |
60 | 3 | 25 | 90 | 50 |
61 | 1 | 5 | 10 | 5 |
61 | 2 | 25 | 50 | 5 |
61 | 3 | 25 | 50 | 5 |
62 | 1 | 25 | 50 | 5 |
62 | 2 | 25 | 50 | 5 |
62 | 3 | 25 | 50 | 5 |
63 | 1 | 25 | 25 | 25 |
63 | 2 | 25 | 90 | 75 |
63 | 3 | 25 | 90 | 75 |
64 | 1 | 25 | 90 | 75 |
64 | 2 | 25 | 90 | 75 |
64 | 3 | 25 | 90 | 75 |
65 | 1 | 50 | 75 | 10 |
65 | 2 | 50 | 75 | 10 |
65 | 3 | 50 | 75 | 10 |
66 | 1 | 50 | 50 | 25 |
66 | 2 | 5 | 75 | 25 |
66 | 3 | 5 | 75 | 25 |
67 | 1 | 5 | 25 | 5 |
67 | 2 | 5 | 25 | 5 |
67 | 3 | 5 | 25 | 5 |
68 | 1 | 5 | 25 | 5 |
68 | 2 | 50 | 95 | 75 |
68 | 3 | 50 | 95 | 75 |
69 | 1 | 50 | 95 | 75 |
69 | 2 | 50 | 95 | 75 |
69 | 3 | 50 | 95 | 75 |
70 | 1 | 25 | 50 | 75 |
70 | 2 | 50 | 95 | 75 |
70 | 3 | 50 | 95 | 75 |
is anybody can help me?
I try to explain the dataset.
I have 70 observation. Variable A, B and C for each subject are measured in three different time point (1,2,3)
In which way can i built the model repeated measures latent class analysis (RMLCA)...
please help me..
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