[R] lme: subject-specific slopes.

[John Sorkin]

Ken,
Thank you for your help. ranef(fitRIRT) does not give me what I expect. The subject-specific slopes, and subject-specific intercepts are not anywhere close to what I would expect them to be; the mean of the subject-specfic values should be close to those reported by 
summary(fitRIRT) and they are not. As you will see by examining the material below, the subject-specific slopes are off by many order of magnitude. The intercepts are also far from the value reported in summary(fitRIRT). Do you have any thoughts?
Thanks,
John
 
> fitRIRT <- lme(echogen~time,random=~  1+time|subject,data=repeatdata,na.action=na.omit)> summary(fitRIRT)Linear mixed-effects model fit by REML
 Data: repeatdata 
      AIC      BIC    logLik
  495.097 507.2491 -241.5485

Random effects:
 Formula: ~1 + time | subject
 Structure: General positive-definite, Log-Cholesky parametrization
            StdDev       Corr  
(Intercept) 1.917511e+01 (Intr)
time        2.032276e-04 0     
Residual    1.044601e+01       

Fixed effects: echogen ~ time 
               Value Std.Error DF   t-value p-value
(Intercept) 64.54864  4.258235 32 15.158543  0.0000
time         0.35795  0.227080 32  1.576307  0.1248
 Correlation: 
     (Intr)
time -0.242

Standardized Within-Group Residuals:
        Min          Q1         Med          Q3         Max 
-1.61362755 -0.52710871  0.02948008  0.41793322  1.77340082 

Number of Observations: 58
Number of Groups: 25 > ranef(fitRIRT)   (Intercept)          time
1    -3.278112  2.221016e-09
2   -35.400618  4.314995e-08
3    11.493110 -6.797543e-09
4   -16.209586 -7.070834e-08
5     3.585227 -2.389705e-08
6     1.614320 -1.967700e-09
7     8.346905  5.827094e-08
8    30.917812 -3.768584e-08
9    -0.394101 -9.158251e-09
10    4.437509 -4.057971e-08
11   31.956597 -2.126275e-08
12   41.567402 -4.853942e-08
13  -10.723993  1.307152e-08
14   -4.554837  5.551908e-09
15   -4.554501  4.815086e-08
16   13.296985 -3.743967e-08
17   -8.255439  1.733238e-08
18  -21.317239  2.203885e-08
19  -13.480159  2.194016e-08
20  -13.044766  2.269168e-08
21   11.639198 -1.418706e-08
22  -27.457388 -1.154099e-08
23    2.194001 -5.509119e-09
24   -3.992646  7.682188e-08
25    1.614320 -1.967700e-09
 
 


 
 
John David Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
(Fax) 410-605-7913 (Please call phone number above prior to faxing)>>> Kenneth Frost <kfrost at wisc.edu> 12/4/2012 10:44 AM >>>
I think this might be close to what you want. ranef(fitRIRT)

On 12/04/12, John Sorkin  wrote:
> I am running a random intercept random slope regression:
> 
> fitRIRT <- lme(echogen~time,random=~ 1+time|subject,data=repeatdata,na.action=na.omit)
> summary(fitRIRT)
> 
> I would like to get the subject-specific slopes, i.e. the slope that the model computes for each subject. If I have 10-subjects I should have 10-slopes. I don't see the slope when I look at the items listed in 
> names(summary(fitRIRT)
> nor when I look at the items listed in 
> names(fitRIRT)
> 
> Thanks 
> John
> 
> 
> 
> 
> 
> 
> John David Sorkin M.D., Ph.D.
> Chief, Biostatistics and Informatics
> University of Maryland School of Medicine Division of Gerontology
> Baltimore VA Medical Center
> 10 North Greene Street
> GRECC (BT/18/GR)
> Baltimore, MD 21201-1524
> (Phone) 410-605-7119
> (Fax) 410-605-7913 (Please call phone number above prior to faxing)
> Confidentiality Statement:
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--
Kenneth Frost
Graduate Research Assistant - Dept. of Plant Pathology
University of Wisconsin - Madison
Lab: (608) 262-9914
Mobile: (608) 556-9637
kfrost at wisc.edu


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