10-30-2024
Yasu
Fluorite | Level 6
Member since
06-23-2011
- 30 Posts
- 1 Likes Given
- 0 Solutions
- 0 Likes Received
-
Latest posts by Yasu
Subject Views Posted 932 01-20-2023 08:25 PM 968 01-20-2023 09:45 AM 1013 01-20-2023 08:19 AM 1035 01-05-2023 09:12 PM 1122 01-05-2023 03:01 AM 2854 04-04-2013 05:49 AM 1809 07-24-2012 04:42 AM 3357 07-02-2012 10:10 PM 2960 06-28-2012 11:38 PM 3357 06-28-2012 01:07 AM -
Activity Feed for Yasu
- Posted Re: Prroc phreg output statement on Statistical Procedures. 01-20-2023 08:25 PM
- Posted Re: Prroc phreg output statement on Statistical Procedures. 01-20-2023 09:45 AM
- Posted Prroc phreg output statement on Statistical Procedures. 01-20-2023 08:19 AM
- Tagged Prroc phreg output statement on Statistical Procedures. 01-20-2023 08:19 AM
- Posted Re: Mixed models for correlated repeated measurement on Statistical Procedures. 01-05-2023 09:12 PM
- Liked Re: Mixed models for correlated repeated measurement for PaigeMiller. 01-05-2023 08:58 PM
- Tagged Mixed models for correlated repeated measurement on Statistical Procedures. 01-05-2023 03:06 AM
- Posted Mixed models for correlated repeated measurement on Statistical Procedures. 01-05-2023 03:01 AM
- Posted Sample size calculation for a non-inferiority trial with POWER procedure on SAS Procedures. 04-04-2013 05:49 AM
- Posted Re: Sample size estimation with PROC POWER on Statistical Procedures. 07-24-2012 04:42 AM
- Posted Re: Analysis of repeated measures data with proc mixed on Statistical Procedures. 07-02-2012 10:10 PM
- Posted Re: Modified H–L χ2 statistic for survival data on Statistical Procedures. 06-28-2012 11:38 PM
- Posted Re: Analysis of repeated measures data with proc mixed on Statistical Procedures. 06-28-2012 01:07 AM
- Posted Re: Modified H–L χ2 statistic for survival data on Statistical Procedures. 06-28-2012 12:32 AM
- Posted Re: Modified H–L χ2 statistic for survival data on Statistical Procedures. 06-28-2012 12:19 AM
- Posted Re: Analysis of repeated measures data with proc mixed on Statistical Procedures. 06-27-2012 12:27 AM
- Posted Re: Analysis of repeated measures data with proc mixed on Statistical Procedures. 06-26-2012 01:55 AM
- Posted Re: Modified H–L χ2 statistic for survival data on Statistical Procedures. 06-22-2012 10:21 PM
- Posted Modified H–L χ2 statistic for survival data on Statistical Procedures. 06-22-2012 06:21 AM
- Posted Analysis of repeated measures data with proc mixed on Statistical Procedures. 06-12-2012 03:37 AM
-
Posts I Liked
Subject Likes Author Latest Post 1
01-20-2023
08:25 PM
They were simulated so that they have weak correlations among them.
... View more
01-20-2023
09:45 AM
Hi Paige,
Thank you for your reply.
They are imaginary variables that are normally distributed. Please imagine that P1_3 and P2_3 are office systolic and diastolic blood pressure, and SP1_3 and SP2_3 are home systolic and diastolic blood pressure.
Thanks,
Yasu
Yasu
... View more
01-20-2023
08:19 AM
Hi,
I'm applying two different cox models to the same dataset.
The linear predictor (XBETA) is different, but the survivor function estimate is exactly the same between two models.
Does this happen by chance?
Below are codes and outputs:
PROC PHREG DATA=&DATA.; CLASS Z/PARAM=REF REF=FIRST; MODEL TIME*EVENT(0)=Z P1_3 P2_3 / RL; OUTPUT OUT=A SURVIVAL=SURV XBETA=XBETA; RUN;
PROC PHREG DATA=&DATA.; CLASS Z/PARAM=REF REF=FIRST; MODEL TIME*EVENT(0)=Z SP1_3 SP2_3 / RL; OUTPUT OUT=B SURVIVAL=SURV XBETA=XBETA; RUN;
... View more
- Tags:
- phreg
01-05-2023
09:12 PM
Sorry, there is a typo in the description of repeated statement. I specified the repeated statement as follows:
repeated bp*visit / type=un subject=id R;
... View more
01-05-2023
03:01 AM
Hi,
I'm trying to analyze correlated repeated measurements (e.g. systolic blood pressure and diastolic blood pressure) with proc MIXED.
I want to analyze both outcomes simultaneously and consider the correlation between variables as that between random effects (random intercepts for each variable).
How should I specify the repeated statement (especially subject= option)?
Below is an example of the data and code that I want to implement .
data bp;
do id=1 to 100;
do bp=1 to 2;
do visit=0 to 4;
input aval @@;
output;
end;
end;
end;
cards;
180 165 155 150 140
110 95 90 85 80
185 175 160 150 135
110 90 85 85 80
...
;
int1=(bp=1);
int2=(bp=2);
run;
proc mixed data=bp;
class id bp visit;
model aval = bp*visit;
random int1 int2 / type=un subject=id G;
repeated visit / type=un subject=id R;
run;
... View more
- Tags:
- mixed
04-04-2013
05:49 AM
Dear all, I'd like to ask you about sample size calculation for a non-inferiority trial with POWER procedure. What is the formula for calculating samplesize used in POWER procedure? Sample SAS code is as follows: PROC POWER; TWOSAMPLEFREQ TEST = PCHI SIDES = U ALPHA = .025 GROUPPROPORTIONS = (.75 .80) NULLPROPORTIONDIFF=-.10 POWER = .8 Ntotal = . ; RUN; Thanks in advance, Yasu
... View more
07-24-2012
04:42 AM
Dear Frankgreen, Thank you for your reply. I almost agree with you, but I don't think that the graph is exact because it is an approximate value. Please submit the example code below. Comparing results, you can see that the estimated value on the graph can be affected by the number of values for the parameter, that is, the precision can differ depending on the option. /*example1*/ proc power; pairedmeans test=equiv_ratio dist=lognormal meanratio = 1.10 alpha = 0.05 cv = 0.15 corr = 0 lower = 0.8 upper = 1.25 npairs = 2 to 100 by 1 power =. ; plot min=2 max=100 yopts=(ref=0.8, 0.9 crossref=yes) ; run; /*example2*/ proc power; pairedmeans test=equiv_ratio dist=lognormal meanratio = 1.10 alpha = 0.05 cv = 0.15 corr = 0 lower = 0.8 upper = 1.25 npairs = 2 to 100 by 1 power =. ; plot min=2 max=100 yopts=(ref=0.8, 0.9 crossref=yes) npts=500; run; regard, yasu
... View more
07-02-2012
10:10 PM
Dear Steve, I really appreciate your continued support ! I'll check with tech support about this. Once agan, thank you for your kind reply. Yasu
... View more
06-28-2012
11:38 PM
Dear PG, Thank you for your usuful information. I'll contact with him by e-mail. Yasu
... View more
06-28-2012
01:07 AM
Dear Steve, I really appreciate your continued support. Looking at the log, it seems to occur at the initial iteration. And I looked into the data once again, but there are no such a record. In addition, I have another question. If there are some duplicate record, why does not the infinite likelihood occur with type=UN specificstions? Thanks, Yasu
... View more
06-28-2012
12:32 AM
Than you for your continued help. Yes, I know the conventional Hosmer-Lomeshow test for binary data can be conducted with lackfit specification in Proc Logistic. But I want to conduct the modified one for survival data. D'Agostino and Nam introduced it and a lot of authers have been refering to this article. So I think SAS macro code can be available or published. Thanks, Yasu
... View more
06-28-2012
12:19 AM
Thank you for your reply. I'm sorry for trouble you. Could you refer to the following article? http://www.sciencedirect.com/science/article/pii/S0169716103230017
... View more
06-27-2012
12:27 AM
The time points are equally spaced for each subject, so I tried type=AR(1) and type=sp(pow)(time1). But the "infinite likelihood" error message occured with both type specification. I'n not sure what is causing the infinite liklihood error yet...
... View more
06-26-2012
01:55 AM
Dear Steve, Thank you for your continued sopport. the covariance estimates under the TYPE=UN specification as follows: Estimated R Matrix for SUBJID 0001-001 Row Col1 Col2 Col3 Col4 Col5 1 331.08 301.34 278.17 269.69 260.96 2 301.34 330.16 302.41 285.32 270.93 3 278.17 302.41 419.88 356.43 283.12 4 269.69 285.32 356.43 473.49 320.51 5 260.96 270.93 283.12 320.51 400.03 Covariance Parameter Estimates Cov Parm Subject Estimate UN(1,1) SUBJID 331.08 UN(2,1) SUBJID 301.34 UN(2,2) SUBJID 330.16 UN(3,1) SUBJID 278.17 UN(3,2) SUBJID 302.41 UN(3,3) SUBJID 419.88 UN(4,1) SUBJID 269.69 UN(4,2) SUBJID 285.32 UN(4,3) SUBJID 356.43 UN(4,4) SUBJID 473.49 UN(5,1) SUBJID 260.96 UN(5,2) SUBJID 270.93 UN(5,3) SUBJID 283.12 UN(5,4) SUBJID 320.51 UN(5,5) SUBJID 400.03 UN(6,1) SUBJID 255.04 UN(6,2) SUBJID 264.57 UN(6,3) SUBJID 276.21 UN(6,4) SUBJID 294.30 UN(6,5) SUBJID 323.57 UN(6,6) SUBJID 373.06 UN(7,1) SUBJID 248.73 UN(7,2) SUBJID 256.85 UN(7,3) SUBJID 274.29 UN(7,4) SUBJID 284.68 UN(7,5) SUBJID 295.96 UN(7,6) SUBJID 310.99 UN(7,7) SUBJID 351.47 UN(8,1) SUBJID 249.61 UN(8,2) SUBJID 257.29 UN(8,3) SUBJID 275.29 UN(8,4) SUBJID 285.32 UN(8,5) SUBJID 296.04 UN(8,6) SUBJID 298.96 UN(8,7) SUBJID 329.12 UN(8,8) SUBJID 360.03 Looking at the covariance estimates under the TYPE=UN specification, the assumption of compound symmetry is no longer valid. I' d really appreciate it if you would give me your inputs. Thanks, Yasu
... View more
06-22-2012
10:21 PM
Dear ballardw, Thank you for your reply and I apologize my explanation was not enough. The H-L statistic stands for the Hosmer-Lemeshow statistic and you can view the reference article at the following link (though it might be the draft version): http://books.google.co.jp/books?hl=ja&lr=&id=oP4ZJxBE1csC&oi=fnd&pg=PA1&dq=Evaluation+of+the+Performance+of+Survival+Analysis+Models:+Discrimination+and+Calibration+Measures&ots=NGZ2ZHObiP&sig=r5ErSjPz9JdfSFsR63F7hR4CSUk#v=onepage&q=Evaluation%20of%20the%20Performance%20of%20Survival%20Analysis%20Models%3A%20Discrimination%20and%20Calibration%20Measures&f=false Your continued support will be greatly appreciated. Yasu
... View more