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st: Interpreting gllamm
From
Malin Lundberg Rasmussen <[email protected]>
To
"'[email protected]'" <[email protected]>
Subject
st: Interpreting gllamm
Date
Tue, 13 Nov 2012 15:41:08 +0100
Dear statalist
I hope you can help me and my lack of statisticcally/STATA knowledge. And have patience; there are questions in the end ;o)
I have a group of patients and have studies their eyes (dependent variables). I want to see if a finding in 1995 can predict an outcome in 2011.
The covariate (ma1995) I am investigating is consisting of continuus data (1-10), the outcome (ret_2011) is a grading level/categorical (level 10-85 (12 levels in all)). And since I am dealing with eyes my data is not independent.
And just a view of my variates:
tab ma1995
ma1995 | Freq. Percent Cum.
------------+-----------------------------------
0 | 1 0.95 0.95
1 | 49 46.67 47.62
2 | 20 19.05 66.67
3 | 12 11.43 78.10
4 | 9 8.57 86.67
5 | 5 4.76 91.43
6 | 5 4.76 96.19
7 | 2 1.90 98.10
10 | 1 0.95 99.05
21 | 1 0.95 100.00
------------+-----------------------------------
Total | 105 100.00
. tab ret_2011
ret_2011 | Freq. Percent Cum.
------------+-----------------------------------
20 | 17 16.19 16.19
35 | 34 32.38 48.57
43 | 15 14.29 62.86
47 | 3 2.86 65.71
61 | 22 20.95 86.67
65 | 9 8.57 95.24
71 | 1 0.95 96.19
75 | 3 2.86 99.05
85 | 1 0.95 100.00
------------+-----------------------------------
Total | 105 100.00
I was told I could use the STATA command gllamm, but I have a problem interpreting the outcome...
I write
gllamm ret_2011 ma1995, i(inr_)
And get the following results:
Iteration 0: log likelihood = -440.63147 (not concave)
Iteration 1: log likelihood = -440.45372
Iteration 2: log likelihood = -416.91371 (not concave)
Iteration 3: log likelihood = -414.37278
Iteration 4: log likelihood = -410.47618
Iteration 5: log likelihood = -410.22201
Iteration 6: log likelihood = -410.22191
Iteration 7: log likelihood = -410.22191
number of level 1 units = 105
number of level 2 units = 73
Condition Number = 8.5127997
gllamm model
log likelihood = -410.22191
------------------------------------------------------------------------------
ret_2011 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
ma1995 | .5467041 .171913 3.18 0.001 .2097609 .8836473
_cons | 40.5618 .6920948 58.61 0.000 39.20532 41.91828
------------------------------------------------------------------------------
Variance at level 1
------------------------------------------------------------------------------
16.905984 (2.8159187)
Variances and covariances of random effects
------------------------------------------------------------------------------
***level 2 (inr_)
var(1): 156.99649 (9.1764146)
------------------------------------------------------------------------------
My questions are:
1) What does 'not concave' mean?
2) What is the "Condition Number"?
3) I have read that the Coef. is the average score - but this doesn't seem to fit (see tab ma1995 above)
4) What is statistically significant (p=0.001)?? - that there is a connection, between ma1995 and the outcome? And if so, can I see what the connection is (e.g. the higher ma1995, the higher ret_2011)
5) and last; what does the last outcome say (variance at level 1 and level 2)??
I am very sorry for my ignorance!
Hoping for some help
Best regards
Malin
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