Re: [R] Trying to make a nested lme analysis
Thanks,
it works:))
Inte
Ronaldo
ps. rats data and others used in book is in the Crawley home page:
http://www.bio.ic.ac.uk/research/mjcraw/statcomp/welcome.htm
Em Douglas Bates, escreveu:
> Where is the rats data available?
>
> It looks as if you have an lme model with both a fixed effect for
> Treatment and a random effect for Treatment. I would guess that you
> want to have a fixed effect for treatment and random effects for
>
> Rat %in% Treatment
>
> and
>
> Liver %in% Rat %in% Treatment
>
> If so you would first create a factor for Rat %in% Treatment, say rTrT
> by
>
> rats$rTrt = getGroups(~ 1 | Treatment/Rat, data = rats, level = 2)
>
> then fit the lme model as
>
> lme(Glycogen ~ Treatment, data = rats, random = ~ 1|rTrT/Liver)
>
> "Ronaldo Reis Jr." <[EMAIL PROTECTED]> writes:
> > Hi,
> >
> > I'm trying to understand the lme output and procedure.
> > I'm using the Crawley's book.
> >
> > I'm try to analyse the rats example take from Sokal and Rohlf (1995).
> > I make a nested analysis using aov following the book.
> >
> > > summary(rats)
> >
> > Glycogen Treatment Rat Liver
> > Min. :125.0 Min. :1 Min. :1.0 Min. :1
> > 1st Qu.:135.8 1st Qu.:1 1st Qu.:1.0 1st Qu.:1
> > Median :141.0 Median :2 Median :1.5 Median :2
> > Mean :142.2 Mean :2 Mean :1.5 Mean :2
> > 3rd Qu.:150.0 3rd Qu.:3 3rd Qu.:2.0 3rd Qu.:3
> > Max. :162.0 Max. :3 Max. :2.0 Max. :3
> >
> > > attach(rats)
> > > Treatment <- factor(Treatment)
> > > Rat <- factor(Rat)
> > > Liver <- factor(Liver)
> > >
> > > model <- aov(Glycogen~Treatment/Rat/Liver+Error(Treatment/Rat/Liver))
> > > summary(model)
> >
> > Error: Treatment
> > Df Sum Sq Mean Sq
> > Treatment 2 1557.56 778.78
> >
> > Error: Treatment:Rat
> > Df Sum Sq Mean Sq
> > Treatment:Rat 3 797.67 265.89
> >
> > Error: Treatment:Rat:Liver
> > Df Sum Sq Mean Sq
> > Treatment:Rat:Liver 12 594.049.5
> >
> > Error: Within
> > Df Sum Sq Mean Sq F value Pr(>F)
> > Residuals 18 381.00 21.17
> >
> >
> > OK,
> >
> > Then I try to make this analysis using lme.
> >
> > > model <- lme(Glycogen~Treatment, random=~1|Treatment/Rat/Liver)
> > > summary(model)
> >
> > Linear mixed-effects model fit by REML
> > Data: NULL
> >AIC BIClogLik
> > 233.6213 244.0968 -109.8106
> >
> > Random effects:
> > Formula: ~1 | Treatment
> > (Intercept)
> > StdDev:3.541272
> >
> > Formula: ~1 | Rat %in% Treatment
> > (Intercept)
> > StdDev: 6.00658
> >
> > Formula: ~1 | Liver %in% Rat %in% Treatment
> > (Intercept) Residual
> > StdDev:3.764883 4.600247
> >
> > Fixed effects: Glycogen ~ Treatment
> > Error in if (any(wchLv <- (as.double(levels(xtTab[, wchPval])) == 0))) {
> > : missing value where logical needed
> > In addition: Warning message:
> > NaNs produced in: pt(q, df, lower.tail, log.p)
> >
> >
> > The random effects are correct, the variance component is OK:
> >
> > In nested aov | In nested lme
> > Residual
> > 21.1666 | 21.16227
> > Liver in Rats
> > 14.16667 | 14.17434
> > Rats in Treatment
> > 36.0648 | 36.079
> >
> > But I not understand why the Fixed effects error?
> >
> > What is the problem in my formula to make this analysis using lme?
> >
> > Thanks for all
> > Inte
> > Ronaldo
> > --
> > Anger kills as surely as the other vices.
> > --
> >
> > | // | \\ [*][***]
> > |
> > || ( õ õ ) [Ronaldo Reis Júnior ][PentiumIII-600 ]
> > |
> > | V [UFV/DBA-Entomologia ][HD: 30 + 10 Gb ]
> > |
> > || / \ [36571-000 Viçosa - MG][RAM: 128 Mb]
> > |
> > | /(.''`.)\ [Fone: 31-3899-2532 ][Video: SiS620-8Mb ]
> > |
> > ||/(: :' :)\ [EMAIL PROTECTED] ][Modem: Pctel-onboar]
> > |
> > |/ (`. `'` ) \[ICQ#: 5692561][Kernel: 2.4.18 ]
> > |
> > || ( `- ) [*][***]
> > ||
> > ||| _/ \_Powered by GNU/Debian W/Sarge D+ || Lxuser#: 205366
> >
> > __
> > [EMAIL PROTECTED] mailing list
> > https://www.stat.math.ethz.ch/mailman/listinfo/r-help
--
O muito torna-se pouco com desejar um pouco mais.
-- Francisco de Quevedo
--
| // | \\ [*][***]
|| ( õ õ ) [Ronaldo Reis Júnior ][PentiumIII-600 ]
| V [UFV/DBA-Entomologia ][HD: 30 + 10 Gb ]
|| / \ [36571-000 Viçosa - MG][RAM: 128 Mb]
| /(.''`.)\ [Fone: 31-3899-2532 ][Video: SiS620-8Mb ]
||/(: :' :)\ [EMAIL PROTECTED] ][Modem: Pctel-onboar]
|/ (`. `'` ) \[ICQ#: 5692561][Kernel: 2.4.18 ]
|| ( `- ) [*][***]
||| _/ \_Powered by GNU/Debian W/Sarge D+ || Lxuser#: 205366
_
Re: [R] Trying to make a nested lme analysis
Where is the rats data available?
It looks as if you have an lme model with both a fixed effect for
Treatment and a random effect for Treatment. I would guess that you
want to have a fixed effect for treatment and random effects for
Rat %in% Treatment
and
Liver %in% Rat %in% Treatment
If so you would first create a factor for Rat %in% Treatment, say rTrT
by
rats$rTrt = getGroups(~ 1 | Treatment/Rat, data = rats, level = 2)
then fit the lme model as
lme(Glycogen ~ Treatment, data = rats, random = ~ 1|rTrT/Liver)
"Ronaldo Reis Jr." <[EMAIL PROTECTED]> writes:
> Hi,
>
> I'm trying to understand the lme output and procedure.
> I'm using the Crawley's book.
>
> I'm try to analyse the rats example take from Sokal and Rohlf (1995).
> I make a nested analysis using aov following the book.
>
> > summary(rats)
> Glycogen Treatment Rat Liver
> Min. :125.0 Min. :1 Min. :1.0 Min. :1
> 1st Qu.:135.8 1st Qu.:1 1st Qu.:1.0 1st Qu.:1
> Median :141.0 Median :2 Median :1.5 Median :2
> Mean :142.2 Mean :2 Mean :1.5 Mean :2
> 3rd Qu.:150.0 3rd Qu.:3 3rd Qu.:2.0 3rd Qu.:3
> Max. :162.0 Max. :3 Max. :2.0 Max. :3
>
> > attach(rats)
> > Treatment <- factor(Treatment)
> > Rat <- factor(Rat)
> > Liver <- factor(Liver)
>
> > model <- aov(Glycogen~Treatment/Rat/Liver+Error(Treatment/Rat/Liver))
> > summary(model)
>
> Error: Treatment
> Df Sum Sq Mean Sq
> Treatment 2 1557.56 778.78
>
> Error: Treatment:Rat
> Df Sum Sq Mean Sq
> Treatment:Rat 3 797.67 265.89
>
> Error: Treatment:Rat:Liver
> Df Sum Sq Mean Sq
> Treatment:Rat:Liver 12 594.049.5
>
> Error: Within
> Df Sum Sq Mean Sq F value Pr(>F)
> Residuals 18 381.00 21.17
> >
>
> OK,
>
> Then I try to make this analysis using lme.
>
> > model <- lme(Glycogen~Treatment, random=~1|Treatment/Rat/Liver)
> > summary(model)
> Linear mixed-effects model fit by REML
> Data: NULL
>AIC BIClogLik
> 233.6213 244.0968 -109.8106
>
> Random effects:
> Formula: ~1 | Treatment
> (Intercept)
> StdDev:3.541272
>
> Formula: ~1 | Rat %in% Treatment
> (Intercept)
> StdDev: 6.00658
>
> Formula: ~1 | Liver %in% Rat %in% Treatment
> (Intercept) Residual
> StdDev:3.764883 4.600247
>
> Fixed effects: Glycogen ~ Treatment
> Error in if (any(wchLv <- (as.double(levels(xtTab[, wchPval])) == 0))) { :
> missing value where logical needed
> In addition: Warning message:
> NaNs produced in: pt(q, df, lower.tail, log.p)
> >
>
> The random effects are correct, the variance component is OK:
>
> In nested aov | In nested lme
> Residual
> 21.1666 | 21.16227
> Liver in Rats
> 14.16667 | 14.17434
> Rats in Treatment
> 36.0648 | 36.079
>
> But I not understand why the Fixed effects error?
>
> What is the problem in my formula to make this analysis using lme?
>
> Thanks for all
> Inte
> Ronaldo
> --
> Anger kills as surely as the other vices.
> --
> | // | \\ [*][***]
> || ( õ õ ) [Ronaldo Reis Júnior ][PentiumIII-600 ]
> | V [UFV/DBA-Entomologia ][HD: 30 + 10 Gb ]
> || / \ [36571-000 Viçosa - MG][RAM: 128 Mb]
> | /(.''`.)\ [Fone: 31-3899-2532 ][Video: SiS620-8Mb ]
> ||/(: :' :)\ [EMAIL PROTECTED] ][Modem: Pctel-onboar]
> |/ (`. `'` ) \[ICQ#: 5692561][Kernel: 2.4.18 ]
> || ( `- ) [*][***]
> ||| _/ \_Powered by GNU/Debian W/Sarge D+ || Lxuser#: 205366
>
> __
> [EMAIL PROTECTED] mailing list
> https://www.stat.math.ethz.ch/mailman/listinfo/r-help
--
Douglas Bates[EMAIL PROTECTED]
Statistics Department608/262-2598
University of Wisconsin - Madisonhttp://www.stat.wisc.edu/~bates/
__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] Trying to make a nested lme analysis
Hi,
I'm trying to understand the lme output and procedure.
I'm using the Crawley's book.
I'm try to analyse the rats example take from Sokal and Rohlf (1995).
I make a nested analysis using aov following the book.
> summary(rats)
Glycogen Treatment Rat Liver
Min. :125.0 Min. :1 Min. :1.0 Min. :1
1st Qu.:135.8 1st Qu.:1 1st Qu.:1.0 1st Qu.:1
Median :141.0 Median :2 Median :1.5 Median :2
Mean :142.2 Mean :2 Mean :1.5 Mean :2
3rd Qu.:150.0 3rd Qu.:3 3rd Qu.:2.0 3rd Qu.:3
Max. :162.0 Max. :3 Max. :2.0 Max. :3
> attach(rats)
> Treatment <- factor(Treatment)
> Rat <- factor(Rat)
> Liver <- factor(Liver)
> model <- aov(Glycogen~Treatment/Rat/Liver+Error(Treatment/Rat/Liver))
> summary(model)
Error: Treatment
Df Sum Sq Mean Sq
Treatment 2 1557.56 778.78
Error: Treatment:Rat
Df Sum Sq Mean Sq
Treatment:Rat 3 797.67 265.89
Error: Treatment:Rat:Liver
Df Sum Sq Mean Sq
Treatment:Rat:Liver 12 594.049.5
Error: Within
Df Sum Sq Mean Sq F value Pr(>F)
Residuals 18 381.00 21.17
>
OK,
Then I try to make this analysis using lme.
> model <- lme(Glycogen~Treatment, random=~1|Treatment/Rat/Liver)
> summary(model)
Linear mixed-effects model fit by REML
Data: NULL
AIC BIClogLik
233.6213 244.0968 -109.8106
Random effects:
Formula: ~1 | Treatment
(Intercept)
StdDev:3.541272
Formula: ~1 | Rat %in% Treatment
(Intercept)
StdDev: 6.00658
Formula: ~1 | Liver %in% Rat %in% Treatment
(Intercept) Residual
StdDev:3.764883 4.600247
Fixed effects: Glycogen ~ Treatment
Error in if (any(wchLv <- (as.double(levels(xtTab[, wchPval])) == 0))) { :
missing value where logical needed
In addition: Warning message:
NaNs produced in: pt(q, df, lower.tail, log.p)
>
The random effects are correct, the variance component is OK:
In nested aov | In nested lme
Residual
21.1666 | 21.16227
Liver in Rats
14.16667 | 14.17434
Rats in Treatment
36.0648 | 36.079
But I not understand why the Fixed effects error?
What is the problem in my formula to make this analysis using lme?
Thanks for all
Inte
Ronaldo
--
Anger kills as surely as the other vices.
--
| // | \\ [*][***]
|| ( õ õ ) [Ronaldo Reis Júnior ][PentiumIII-600 ]
| V [UFV/DBA-Entomologia ][HD: 30 + 10 Gb ]
|| / \ [36571-000 Viçosa - MG][RAM: 128 Mb]
| /(.''`.)\ [Fone: 31-3899-2532 ][Video: SiS620-8Mb ]
||/(: :' :)\ [EMAIL PROTECTED] ][Modem: Pctel-onboar]
|/ (`. `'` ) \[ICQ#: 5692561][Kernel: 2.4.18 ]
|| ( `- ) [*][***]
||| _/ \_Powered by GNU/Debian W/Sarge D+ || Lxuser#: 205366
__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] Trying to make a nested lme analysis
Hi,
I'm trying to understand the lme output and procedure.
I'm using the Crawley's book.
I'm try to analyse the rats example take from Sokal and Rohlf (1995).
I make a nested analysis using aov following the book.
> summary(rats)
Glycogen Treatment Rat Liver
Min. :125.0 Min. :1 Min. :1.0 Min. :1
1st Qu.:135.8 1st Qu.:1 1st Qu.:1.0 1st Qu.:1
Median :141.0 Median :2 Median :1.5 Median :2
Mean :142.2 Mean :2 Mean :1.5 Mean :2
3rd Qu.:150.0 3rd Qu.:3 3rd Qu.:2.0 3rd Qu.:3
Max. :162.0 Max. :3 Max. :2.0 Max. :3
> attach(rats)
> Treatment <- factor(Treatment)
> Rat <- factor(Rat)
> Liver <- factor(Liver)
> model <- aov(Glycogen~Treatment/Rat/Liver+Error(Treatment/Rat/Liver))
> summary(model)
Error: Treatment
Df Sum Sq Mean Sq
Treatment 2 1557.56 778.78
Error: Treatment:Rat
Df Sum Sq Mean Sq
Treatment:Rat 3 797.67 265.89
Error: Treatment:Rat:Liver
Df Sum Sq Mean Sq
Treatment:Rat:Liver 12 594.049.5
Error: Within
Df Sum Sq Mean Sq F value Pr(>F)
Residuals 18 381.00 21.17
>
OK,
Then I try to make this analysis using lme.
> model <- lme(Glycogen~Treatment, random=~1|Treatment/Rat/Liver)
> summary(model)
Linear mixed-effects model fit by REML
Data: NULL
AIC BIClogLik
233.6213 244.0968 -109.8106
Random effects:
Formula: ~1 | Treatment
(Intercept)
StdDev:3.541272
Formula: ~1 | Rat %in% Treatment
(Intercept)
StdDev: 6.00658
Formula: ~1 | Liver %in% Rat %in% Treatment
(Intercept) Residual
StdDev:3.764883 4.600247
Fixed effects: Glycogen ~ Treatment
Error in if (any(wchLv <- (as.double(levels(xtTab[, wchPval])) == 0))) {
:
missing value where logical needed
In addition: Warning message:
NaNs produced in: pt(q, df, lower.tail, log.p)
>
The random effects are correct, the variance component is OK:
In nested aov | In nested lme
Residual
21.1666 | 21.16227
Liver in Rats
14.16667 | 14.17434
Rats in Treatment
36.0648 | 36.079
But I not understand why the Fixed effects error?
What is the problem in my formula to make this analysis using lme?
Thanks for all
Inte
Ronaldo
--
| //|\\ [*]
|| ( õ õ ) [Ronaldo Reis Júnior ]
| V [ESALQ/USP-Entomologia, CP-09 ]
|| / l \ [13418-900 Piracicaba - SP]
| /(lin)\ [Fone: 19-429-4199 r.229 ]
||/(linux)\ [EMAIL PROTECTED] ]
|/ (linux) \[ICQ#: 5692561]
|| ( x ) [*]
||| _/ \_ Powered by Gnu/Debian Woody
---
Insecta - Entomologia
Departamento de Biologia Animal
Universidade Federal de Viçosa
---
__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
