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: This email message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply email and destroy all copies of the original message.
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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 Confidentiality Statement: This email message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply email and destroy all copies of the original message.