[R] lme, groupedData, random intercept and slope

2010-09-10 Thread John Sorkin 
Windows Vista
R 2.10.1




Does the following use of groupedData and lme produce an analysis with both 
random intercept and slope, or only random slope?


zz-groupedData(y~time |  Subject,data=data.frame(data),
  labels = list( x = Time,
y = y ),
  units = list( x = (yr), y = (mm))
)
plot(zz)

fit10-lme(zz)
summary(fit10)

Linear mixed-effects model fit by REML
 Data: zz 
AIC   BIC  logLik
  -123.1942 -115.2010 67.5971

Random effects:
 Formula: ~time | Subject
 Structure: General positive-definite
StdDev   Corr  
(Intercept) 6.054897e+00 (Intr)
time4.160662e-05 1 
Residual9.775954e-04   

Fixed effects: y ~ time 
Value Std.Error DF   t-value p-value
(Intercept) 15.000217  1.914727 19 7.834   0
time-1.51  0.000219 19 -4566.598   0
 Correlation: 
 (Intr)
time 0.059 

Standardized Within-Group Residuals:
Min  Q1 Med  Q3 Max 
-1.73706837 -0.36289558  0.06892484  0.59777067  1.69095476 

Number of Observations: 30
Number of Groups: 10 


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 th...{{dropped:6}}

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Re: [R] lme, groupedData, random intercept and slope

2010-09-10 Thread array chip 
from the output, I think it's both.



- Original Message 
From: John Sorkin jsor...@grecc.umaryland.edu
To: r-help@r-project.org
Sent: Fri, September 10, 2010 5:25:44 AM
Subject: [R] lme, groupedData, random intercept and slope

Windows Vista
R 2.10.1




Does the following use of groupedData and lme produce an analysis with both 
random intercept and slope, or only random slope?


zz-groupedData(y~time |  Subject,data=data.frame(data),
  labels = list( x = Time,
y = y ),
  units = list( x = (yr), y = (mm))
)
plot(zz)

fit10-lme(zz)
summary(fit10)

Linear mixed-effects model fit by REML
Data: zz 
AIC   BIC  logLik
  -123.1942 -115.2010 67.5971

Random effects:
Formula: ~time | Subject
Structure: General positive-definite
StdDev   Corr  
(Intercept) 6.054897e+00 (Intr)
time4.160662e-05 1
Residual9.775954e-04  

Fixed effects: y ~ time 
Value Std.Error DF   t-value p-value
(Intercept) 15.000217  1.914727 19 7.834   0
time-1.51  0.000219 19 -4566.598   0
Correlation: 
 (Intr)
time 0.059 

Standardized Within-Group Residuals:
Min  Q1 Med  Q3 Max 
-1.73706837 -0.36289558  0.06892484  0.59777067  1.69095476 

Number of Observations: 30
Number of Groups: 10 


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 th...{{dropped:12}}

__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.