10-07-2017
mahmood
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06-29-2017
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Latest posts by mahmood
Subject Views Posted 2665 09-15-2017 03:08 PM 2719 09-14-2017 11:41 AM 2720 09-14-2017 11:40 AM 2723 09-14-2017 11:30 AM 2727 09-14-2017 11:19 AM 2731 09-14-2017 11:14 AM 2753 09-14-2017 10:29 AM 1529 09-14-2017 10:25 AM 4004 09-13-2017 12:52 PM 4026 09-13-2017 11:21 AM -
Activity Feed for mahmood
- Posted Re: Proc mixed G matrix (random intercept) on Statistical Procedures. 09-15-2017 03:08 PM
- Posted Re: Proc mixed G matrix (random intercept) on Statistical Procedures. 09-14-2017 11:41 AM
- Posted Re: Proc mixed G matrix (random intercept) on Statistical Procedures. 09-14-2017 11:40 AM
- Posted Re: Proc mixed G matrix (random intercept) on Statistical Procedures. 09-14-2017 11:30 AM
- Posted Re: Proc mixed G matrix (random intercept) on Statistical Procedures. 09-14-2017 11:19 AM
- Posted Re: Proc mixed G matrix (random intercept) on Statistical Procedures. 09-14-2017 11:14 AM
- Posted Proc mixed G matrix (random intercept) on Statistical Procedures. 09-14-2017 10:29 AM
- Posted Re: proc mixed with imputated (multiple) data on Statistical Procedures. 09-14-2017 10:25 AM
- Posted Re: Live chat with agent on SAS Programming. 09-13-2017 12:52 PM
- Posted Live chat with agent on SAS Programming. 09-13-2017 11:21 AM
- Posted proc mixed with imputated (multiple) data on Statistical Procedures. 09-13-2017 10:55 AM
- Posted Re: PROC MI: the listing order of the variables in var statement on Statistical Procedures. 07-08-2017 01:32 PM
- Posted Re: Multilevel Imputation on SAS Programming. 06-29-2017 11:41 AM
- Posted Multilevel Imputation on SAS Programming. 06-29-2017 10:48 AM
09-15-2017
03:08 PM
Hello, It seems that the G matrix only prints for the first observation. However, for the R matrix we can select which observations. Thanks, Rahid Mahmood
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09-14-2017
11:41 AM
on previous syntax: i is individual, and t = time
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09-14-2017
11:40 AM
sorry, the actual syntax: model depression = financial_stress personal_rel_stress other_stress VPA age with_both_parents fin_stress_M perso_stress_M other_stress_M VPA_M age_M female mother_university ln_density_house self_esteem parent_born_canada /solution ddfm = bw residual ;
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09-14-2017
11:30 AM
NEW_PIN is the ID
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09-14-2017
11:19 AM
converged well; no warning or notice on the log
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09-14-2017
11:14 AM
Hi, following is the code. x1, x2, x3 are time-variant; x1_mean x2_mean x3_mean are individual mean over time; z are time-invariant. proc mixed data = reg_fin_1 noitprint PLOTS(MAXPOINTS= 20000000000) ; class ID ; by _imputation_ ; model Y_i,t = x1_i,t x2_i,t x3_i,t x1_mean x2_mean x3_mean z1 z2 z3 /solution ddfm = bw residual ; random intercept / subject = ID type = un solution g ; ods output solutionF=mxparms3 ; run;
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09-14-2017
10:29 AM
Hello, Thanks to everyone. I have a question on Proc mixed: I am using longitudinal/panel data. I have a random intercept model and the G matrix I am getting shows (only) row one for the first ID. Is this correct? How can I explain this? Estimated G Matrix Row Effect NEW_PIN Col1 1 Intercept 10001 0.1448
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09-14-2017
10:25 AM
Hello, Thanks to everyone. This "error" has been solved: the problem was due to the organization the imputed data properly. Howeve, I have another question: First of all, this is a longitudinal/panel data. I have a random intercept model and the G matrix I am getting shows (only) row one for the first ID: Estimated G Matrix Row Effect NEW_PIN Col1 1 Intercept 10001 0.1448
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09-13-2017
11:21 AM
Hello, As far as I know, there is a way to chat with an agent but I can't find how to do it. Would anyone help please? Thanks Rahid
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09-13-2017
10:55 AM
Hello, I have got a problem and wondering if someone can help me please. I am trying Proc Mixed with the random intercept: and getting a problem. I have done multiple imputation (so, there are 10, for example _imputation_ = 1 ...._imputation_ = 10). The proc mixed is as follows (variable names are just for example): proc sort data = reg_fin_1 ; by _imputation_ ID ; run; proc mixed data = reg_fin_1 noitprint PLOTS(MAXPOINTS= 20000000000) ; class ID ; by _imputation_ ; model Y = x1 x2 x3 /solution ddfm = bw residual ; random intercept / subject = NEW_PIN type = un ; ods output solutionF=mxparms3 ; run; The problem is that I get the following message: Estimated G matrix is not positive definite. The above message was for the following BY group: _imputation_=1 Estimated G matrix is not positive definite. The above message was for the following BY group: _imputation_=2 ...... ....... However, I don't get this notice when I run proc mixed with the complete cases: I mean, excluded the missing values, hence no imputation, and unlike the multiple imputation I have one dataset. Thanks to all. Rahid
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07-08-2017
01:32 PM
Hello, Thanks for this useful discussion. I have a related question: do I have to put the dependent (outcome) variable first and then all independent variables? I mean, my (mianalyze) model is y = b1*x1 + b2*x2.... How proc mi could understand wich one is the dependent varaiable? Or how FCS is able to identify which one is the dependent/ouctome variable? Would anyone help please? Rahid
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06-29-2017
10:48 AM
Hello, I learned that there is a SAS macro for Mutilevel Imputation called "MMI_IMPUTE". Is there any way that I can get this macro? Would anyone help me please? Thanks, Rahid Mahmood
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