Caros Amigos, Fiz uma análise de regressão utilizando o modelo de efeito misto. Eu desejo fazer o coeficiente de determinação parcial conforme descrito no livro do Kutner, et al (Applied linear statistical Models, ) <http://www.amazon.com/Applied-Linear-Statistical-Models-Michael/dp/007310874X> 5° edição, paginas 268-269 para obter uma estimativa de quanto cada variável incluída no modelo contribuiu para o R2 geral ( ou seja a contribuição marginal de cada variável para a redução da variação quando todas as outras variáveis estão no modelo- No livro é chamado de coeficiente parcial de determinação). O R2 do modelo deve ser igual a soma do R2 parcial de cada variável individualment (R2modelo= R2variável1+R2variável2...). Fiz uma função para automatizar os passos descritos no livro, como vocês poderão ver a soma do R2 parcial de cada variável difere do R2 geral do modelo. Acredito que eu possa ter entendido algo errado, por isso gostaria de ajuda. Alguém da lista ja fez este tipo de avaliação? DATA<- structure(list(DATA = structure(c(25L, 27L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 26L, 28L, 25L, 27L), .Label = c("01/09/13", "02/09/13", "03/09/13", "04/09/13", "05/09/13", "07/09/13", "08/09/13", "10/09/13", "11/09/13", "14/09/13", "15/09/13", "16/09/13", "17/09/13", "18/09/13", "19/09/13", "20/09/13", "21/09/13", "22/09/13", "23/09/13", "24/09/13", "25/09/13", "26/09/13", "27/09/13", "28/09/13", "29/08/13", "29/09/13", "30/08/13", "30/09/13"), class = "factor"), GEST = c(63L, 64L, 66L, 67L, 68L, 69L, 70L, 72L, 73L, 75L, 76L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 88L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 63L, 64L), MANEJO = c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), DIAS = c(1L, 2L, 4L, 5L, 6L, 7L, 8L, 10L, 11L, 13L, 14L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 1L, 2L), ANIMAL = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L), .Label = c("5", "4"), class = c("ordered", "factor")), CONSUMO = c(1.43, 1.24, 2, 1.29, 0.94, 1.99, 1.48, 1.25, 1.8, 2.16, 1.36, 1.33, 2.25, 1.1, 1.78, 1.47, 2, 2.07, 1.35, 1.84, 1.86, 1.5, 1.31, 1.45, 1.46, 2.51, 2.77, 1.89, 1.39, 1.68), PV = c(40, 40.06, 40.18, 40.24, 40.3, 40.36, 40.42, 40.54, 40.6, 40.72, 40.78, 40.99, 41.04, 41.08, 41.13, 41.17, 41.22, 41.26, 41.31, 41.35, 41.4, 41.45, 41.49, 41.54, 41.58, 41.63, 41.67, 41.9, 32.3, 32.47), TEMPMIN = c(11.85, 11.85, 17.9, 18.45, 18.6, 19.6, 19.2, 17.8, 18.7, 15.5, 15.55, 18.7, 18.15, 17.55, 17.85, 18.75, 20.95, 19.3, 19.35, 19.4, 18.8, 17.65, 17.75, 16.45, 16.95, 18.4, 21.1, 18.2, 11.85, 11.85), TEMPMAX = c(28.05, 28.05, 30, 30.9, 30.8, 30.35, 31.2, 27.9, 31.3, 28.6, 28.25, 31.95, 32.75, 30.7, 31.65, 32.85, 32.65, 33.2, 33.05, 24.7, 24.35, 24.95, 28, 28.15, 30.9, 33.1, 34.95, 26.65, 28.05, 28.05), URAMIN = c(38, 38, 40, 41.5, 43, 42.5, 41, 61.5, 44.5, 41.5, 41, 18, 19.5, 26.5, 19.5, 19.5, 20, 25.5, 29, 70, 71.5, 42.5, 50, 44, 31, 23, 15.65, 46.5, 38, 38), URAMAX = c(89, 89, 94, 91, 91, 96.5, 94.5, 99, 95.5, 91, 93, 74.5, 74.5, 75.5, 77, 76, 80, 88, 92, 94, 93.5, 94, 91.5, 85.5, 83.5, 79, 51.75, 77.5, 89, 89), TEMPMEC = c(19.95, 19.95, 23.95, 24.68, 24.7, 24.98, 25.2, 22.85, 25, 22.05, 21.9, 25.33, 25.45, 24.13, 24.75, 25.8, 26.8, 26.25, 26.2, 22.05, 21.58, 21.3, 22.88, 22.3, 23.93, 25.75, 28.03, 22.43, 19.95, 19.95), URAMED = c(63.5, 63.5, 66.25, 69.5, 67.75, 80.25, 70, 67, 47.75, 47, 48.25, 56.75, 60.5, 82.5, 68.25, 70.75, 64.75, 51, 63.5, 62, 56.75, 84.25, 84.25, 64.25, 64.5, 57.75, 72.25, 74.75, 63.5, 63.5 ), ITH = c(4, 4, 151, 220, 212, 304, 267, 82, 133, 20, 16, 201, 231, 246, 218, 317, 343, 230, 302, 40, 21, 49, 147, 51, 143, 238, 409, 82, 4, 4), IMS = c(0.9, 0.62, 0.69, 1.62, 0.81, 1.16, 1.45, 0.87, 0.86, 0.86, 1.04, 1.68, 0.68, 0.56, 1.47, 1.04, 1.14, 0.66, 0.97, 1.35, 1.14, 1.05, 1.52, 0.77, 0.95, 0.84, 1.31, 1.52, 1, 1.37), cook = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)), .Names = c("DATA", "GEST", "MANEJO", "DIAS", "ANIMAL", "CONSUMO", "PV", "TEMPMIN", "TEMPMAX", "URAMIN", "URAMAX", "TEMPMEC", "URAMED", "ITH", "IMS", "cook"), row.names = c("178", "179", "181", "182", "183", "184", "185", "187", "188", "190", "191", "194", "195", "196", "197", "198", "199", "200", "201", "202", "203", "204", "205", "206", "207", "208", "209", "210", "211", "212"), class = c("nffGroupedData", "nfGroupedData", "groupedData", "data.frame"), formula = CONSUMO ~ I(PV^0.75) + IMS + GEST + TEMPMAX + TEMPMIN + URAMIN + URAMAX + as.numeric(ITH) | ANIMAL, FUN = function (x) max(x, na.rm = TRUE), order.groups = TRUE) modelocompleto<-lme(fixed=CONSUMO~GEST+as.numeric(ITH),data=DATA,correlation=corAR1(form=~GEST|ANIMAL),na.action=na.omit,weights=varIdent(form=~1|ANIMAL),random=~1|ANIMAL,method="REML") modeloreduzidoGEST<-update(modelocompleto,fixed=CONSUMO~as.numeric(ITH),random=~1|ANIMAL,method="REML",control=ctrl) modeloreduzidoITH<-update(modelocompleto,fixed=CONSUMO~GEST,random=~1|ANIMAL,method="REML",control=ctrl) R2partial<-function(modelocompleto,modeloreduzidoGEST,modeloreduzidoITH){ SSRGEST<-(sum(resid(modeloreduzidoGEST)^2) - sum(resid(modelocompleto)^2)) SSRITH<-(sum(resid(modeloreduzidoITH)^2) - sum(resid(modelocompleto)^2)) SSEGEST<-sum(resid(modeloreduzidoGEST)^2) SSEITH<-sum(resid(modeloreduzidoITH)^2) R2partialGEST<-SSRGEST/SSEGEST R2partialITH<-SSRITH/SSEITH resultado1<-paste("R2parcial-GEST",R2partialGEST,sep=":") resultado2<-paste("R2parcial-ITH",R2partialITH,sep=":") R2total<-paste("R2total",sum(R2partialGEST,R2partialITH),sep=":") return(c(resultado1,resultado2,R2total)) } R2partial(modelocompleto,modeloreduzidoGEST,modeloreduzidoITH) # R2 parcial para cada uma das vaiáveis install.packages("MuMIn") library(MuMIn) r.squaredGLMM(modeloreduzidoGEST) #R2 Geral