From: Sundar Dorai-Raj <sundar.dorai-raj_at_pdf.com>

Date: Fri, 14 Mar 2008 12:40:57 -0700

> Linear mixed-effects model fit by REML

*> Data: data1
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*> AIC BIC logLik
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*> 25.38958 26.18399 -2.694789
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*>
*

*> Random effects:
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*> Formula: ~1 | Block
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*> (Intercept) Residual
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*> StdDev: 0.1421141 0.218483
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*>
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*> Fixed effects: LCU ~ ST1 * SURF
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*> Value Std.Error DF t-value p-value
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*> (Intercept) 6.470 0.1842977 7 35.10625 0.0000
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*> ST1B 0.220 0.2184830 7 1.00694 0.3475
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*> ST1C 0.100 0.2184830 7 0.45770 0.6610
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*> ST1D -0.125 0.2184830 7 -0.57213 0.5851
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*> SURFY 0.430 0.2184830 7 1.96812 0.0897
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*> ST1B:SURFY -0.240 0.3089816 7 -0.77675 0.4627
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*> ST1C:SURFY -0.080 0.3089816 7 -0.25892 0.8031
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*> ST1D:SURFY 0.175 0.3089816 7 0.56638 0.5888
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*>
*

*> Without the random effect:
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*>
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*> Anal2<-lme(LCU~ST1*SURF,data=data1)
*

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

*> Invalid formula for groups
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*> Classification: UNCLASSIFIED
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*> Caveats: NONE
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*>
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*>
*

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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 Fri 14 Mar 2008 - 19:56:49 GMT

Date: Fri, 14 Mar 2008 12:40:57 -0700

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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