Thanks, Austin, I think that probably clears it up (see below).
On 19-Dec-04 Austin, Matt wrote:
Is it the PBIB dataset in the SASmixed package? I don't have my copy of the text at home.
--Matt
library(SASmixed)
Loading required package: lme4
Attaching package 'lme4':
The following object(s) are masked from package:nlme :
Alfalfa Assay bdf BodyWeight Cefamandole Dialyzer
Earthquake ergoStool Fatigue Gasoline getCovariateFormula
getResponseFormula Glucose Glucose2 Gun IGF lmeControl Machines
MathAchieve MathAchSchool Meat Milk Muscle Nitrendipene Oats
Orthodont Ovary Oxboys Oxide PBG Phenobarb Pixel Quinidine Rail
RatPupWeight Relaxin Remifentanil Soybean Spruce Tetracycline1
Tetracycline2 Wafer Wheat Wheat2
The dataset names in the above masked objects are the entire list of datasets in P&B except for CO2, ChickWeight, DNase, Indometh, Loblolly, Orange and Theoph, and also PBIB. All of these except PBIB can be found elsewhere, but (as you show below) PBIB can be found in SASmixed and so completes the party.
However, SASmixed itself cannot be found the the R Full Reference Manual (of 25 Nov 2004) either ... the dates on the current versions of lme3 and SASmixed are 2004-12-16 and 2004-12-15 respectively. Now that I try it (today), the "R Site Search" of Jonathan Baron does bring it up.
Thanks for helping to clarify this! Ted.
This is a new version of SASmixed that was uploaded a couple of days ago. I changed it so that the fits are done with the lme4 version of lme. It should be faster and more reliable than the version of lme in the nlme package.
This version of SASmixed has a vignette that provides comparative analyses in lme for the examples in "SAS System for Mixed Models". The specification of models in the new lme is occasionally different from the older specification. Don't pay too much attention to the textual descriptions - look at the examples in the appendices. I haven't finished rewriting the textual description from an old, old version.
Those who (like me) cringe at the way that models with crossed random effects needed to be specified in the old lme may find it interesting that the Demand example now specifies the model fit as
Demand> fm1Demand <- lme(log(d) ~ log(y) + log(rd) + log(rt) +
log(rs), data = Demand, random = list(State = ~1, Year = ~1))
Demand> summary(fm1Demand)
Linear mixed-effects model fit by REML
Fixed: log(d) ~ log(y) + log(rd) + log(rt) + log(rs)
Data: Demand
AIC BIC logLik
-224.1653 -205.4148 120.0826Random effects: Groups Name Variance Std.Dev. Year (Intercept) 0.00026465 0.016268 State (Intercept) 0.02948900 0.171724 Residual 0.00111705 0.033422 # of obs: 77, groups: Year, 11; State, 7
Fixed effects:
Estimate Std. Error DF t value Pr(>|t|)
(Intercept) -1.284043 0.723423 72 -1.7750 0.080132 .
log(y) 1.069806 0.103925 72 10.2941 8.553e-16 ***
log(rd) -0.295342 0.052463 72 -5.6296 3.265e-07 ***
log(rt) 0.039882 0.027889 72 1.4300 0.157034
log(rs) -0.326739 0.114385 72 -2.8565 0.005595 **
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1Correlation of Fixed Effects:
(Intr) log(y) lg(rd) lg(rt)
log(y) -0.976
log(rd) 0.383 -0.227
log(rt) 0.077 -0.062 -0.337
log(rs) 0.444 -0.600 -0.270 -0.323The lme4 and nlme packages should not be loaded simultaneously. Use one or the other but not both.
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