From: Simon Blomberg <s.blomberg1_at_uq.edu.au>

Date: Sat, 15 Mar 2008 17:31:45 +1000

> Linear mixed-effects model fit by REML

*> Data: data1
*

*> AIC BIC logLik
*

*> 25.38958 26.18399 -2.694789
*

*>
*

*> Random effects:
*

*> Formula: ~1 | Block
*

*> (Intercept) Residual
*

*> StdDev: 0.1421141 0.218483
*

*>
*

*> Fixed effects: LCU ~ ST1 * SURF
*

*> Value Std.Error DF t-value p-value
*

*> (Intercept) 6.470 0.1842977 7 35.10625 0.0000
*

*> ST1B 0.220 0.2184830 7 1.00694 0.3475
*

*> ST1C 0.100 0.2184830 7 0.45770 0.6610
*

*> ST1D -0.125 0.2184830 7 -0.57213 0.5851
*

*> SURFY 0.430 0.2184830 7 1.96812 0.0897
*

*> ST1B:SURFY -0.240 0.3089816 7 -0.77675 0.4627
*

*> ST1C:SURFY -0.080 0.3089816 7 -0.25892 0.8031
*

*> ST1D:SURFY 0.175 0.3089816 7 0.56638 0.5888
*

*>
*

*> Without the random effect:
*

*>
*

*> Anal2<-lme(LCU~ST1*SURF,data=data1)
*

*> Error in getGroups.data.frame(dataMix, groups) :
*

*> Invalid formula for groups
*

*> Classification: UNCLASSIFIED
*

*> Caveats: NONE
*

*>
*

*>
*

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R-help_at_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. Received on Sat 15 Mar 2008 - 07:38:51 GMT

Date: Sat, 15 Mar 2008 17:31:45 +1000

There's a trick with this: you need to make sure you are using anova.lme rather than anova.lm. So if in this example you do

anova(fit0, fit)

you will get an error.

Simon.

Simon Blomberg, BSc (Hons), PhD, MAppStat.
Lecturer and Consultant Statistician

Faculty of Biological and Chemical Sciences
The University of Queensland

St. Lucia Queensland 4072

Australia

T: +61 7 3365 2506

email: S.Blomberg1_at_uq.edu.au

Policies:

1. I will NOT analyse your data for you.
2. Your deadline is your problem.

The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. - John Tukey.

-----Original Message-----

From: r-help-bounces_at_r-project.org on behalf of Sundar Dorai-Raj
Sent: Sat 15/03/2008 5:40 AM

To: Park, Kyong H Mr ECBC

Cc: 'r-help_at_r-project.org'

Subject: Re: [R] Lme does not work without a random effect (UNCLASSIFIED)

Park, Kyong H Mr ECBC said the following on 3/14/2008 12:25 PM:

*> Classification: UNCLASSIFIED
**> Caveats: NONE
**>
*

> Dear R users,

*>
**> I'm interested in finding a random effect of the Block in the data shown
**> below, but 'lme' does not work without the random effect. I'm not sure how
**> to group the data without continuous value which is shown in the error
**> message at the bottom line. If I use 'aov' with Error(Block), is there a
**> test method comparing between with and without the Block random effect. I'm
**> using R 2.4.1.
**>
**> Appreciate your help.
**>
**> Kyong
**>
**> LCU ST1 SURF Block
**> 1 6.71 A N 1
**> 2 6.97 A Y 1
**> 3 6.77 B N 1
**> 4 6.90 B Y 1
**> 5 6.63 C N 1
**> 6 6.94 C Y 1
**> 7 6.79 D N 1
**> 8 6.93 D Y 1
**> 9 6.23 A N 2
**> 10 6.83 A Y 2
**> 11 6.61 B N 2
**> 12 6.86 B Y 2
**> 13 6.51 C N 2
**> 14 6.90 C Y 2
**> 15 5.90 D N 2
**> 16 6.97 D Y 2
**>
**> A result with the random effect:
**>
**> Anal1<-lme(LCU~ST1*SURF,random=~1|Block,data=data1)
*

>> summary(Anal1)

> Linear mixed-effects model fit by REML

Use "lm" to fit the model without random effect and use anova to compare:

z <- read.table(con <- textConnection(" LCU ST1 SURF Block 1 6.71 A N 1 2 6.97 A Y 1 3 6.77 B N 1 4 6.90 B Y 1 5 6.63 C N 1 6 6.94 C Y 1 7 6.79 D N 1 8 6.93 D Y 1 9 6.23 A N 2 10 6.83 A Y 2 11 6.61 B N 2 12 6.86 B Y 2 13 6.51 C N 2 14 6.90 C Y 2 15 5.90 D N 2 16 6.97 D Y 2"), header = TRUE)close(con)

library(nlme)

fit <- lme(LCU~ST1*SURF,random=~1|Block,data=z)
fit0 <- lm(LCU~ST1*SURF,data=z)

anova(fit, fit0)

**HTH,
**
--sundar

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