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 12 594.0 49.5 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 BIC logLik 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. -- | // | \\ [*****************************][*******************] || ( ? ? ) [Ronaldo Reis J?nior ][PentiumIII-600 ] | V [UFV/DBA-Entomologia ][HD: 30 + 10 Gb ] || / \ [36571-000 Vi?osa - MG ][RAM: 128 Mb ] | /(.''''`.)\ [Fone: 31-3899-2532 ][Video: SiS620-8Mb ] ||/(: :'' :)\ [chrysopa at insecta.ufv.br ][Modem: Pctel-onboar] |/ (`. `''` ) \[ICQ#: 5692561 ][Kernel: 2.4.18 ] || ( `- ) [*****************************][*******************] ||| _/ \_Powered by GNU/Debian W/Sarge D+ || Lxuser#: 205366
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 12 594.0 49.5 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 BIC logLik 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 -- | //|\\ [*****************************] || ( ? ? ) [Ronaldo Reis J?nior ] | V [ESALQ/USP-Entomologia, CP-09 ] || / l \ [13418-900 Piracicaba - SP ] | /(lin)\ [Fone: 19-429-4199 r.229 ] ||/(linux)\ [chrysopa at insecta.ufv.br ] |/ (linux) \[ICQ#: 5692561 ] || ( x ) [*****************************] ||| _/ \_ Powered by Gnu/Debian Woody ----------------------------------- Insecta - Entomologia Departamento de Biologia Animal Universidade Federal de Vi?osa -----------------------------------
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." <chrysopa at insecta.ufv.br> 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 12 594.0 49.5 > > 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 BIC logLik > 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. > -- > | // | \\ [*****************************][*******************] > || ( ? ? ) [Ronaldo Reis J?nior ][PentiumIII-600 ] > | V [UFV/DBA-Entomologia ][HD: 30 + 10 Gb ] > || / \ [36571-000 Vi?osa - MG ][RAM: 128 Mb ] > | /(.''`.)\ [Fone: 31-3899-2532 ][Video: SiS620-8Mb ] > ||/(: :' :)\ [chrysopa at insecta.ufv.br ][Modem: Pctel-onboar] > |/ (`. `'` ) \[ICQ#: 5692561 ][Kernel: 2.4.18 ] > || ( `- ) [*****************************][*******************] > ||| _/ \_Powered by GNU/Debian W/Sarge D+ || Lxuser#: 205366 > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help-- Douglas Bates bates at stat.wisc.edu Statistics Department 608/262-2598 University of Wisconsin - Madison http://www.stat.wisc.edu/~bates/