R help - Mar 2008 - Lme does not work without a random effect (UNCLASSIFIED)

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
 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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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
>  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
> 
> 
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