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From |
Malin Lundberg Rasmussen <Malin.Lundberg.Rasmussen@ouh.regionsyddanmark.dk> |

To |
"'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu> |

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 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

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