Análise de VCU de soja
##-----------------------------------------------------------------------------
## Definições da sessão.
## Lista de pacotes a serem usados na sessão.
pkg <- c("lattice", "latticeExtra", "doBy", "multcomp", "lme4", "plyr",
"gridExtra", "aod", "wzRfun")
sapply(pkg, require, character.only=TRUE)
## lattice latticeExtra doBy multcomp lme4 plyr
## TRUE TRUE TRUE TRUE TRUE TRUE
## gridExtra aod wzRfun
## TRUE TRUE TRUE
sessionInfo()
## R version 3.1.1 (2014-07-10)
## Platform: i686-pc-linux-gnu (32-bit)
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=pt_BR.UTF-8
## [4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=pt_BR.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=pt_BR.UTF-8 LC_NAME=C LC_ADDRESS=C
## [10] LC_TELEPHONE=C LC_MEASUREMENT=pt_BR.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] grid methods splines stats graphics grDevices utils datasets
## [9] base
##
## other attached packages:
## [1] wzRfun_0.3 aod_1.3 gridExtra_0.9.1 plyr_1.8.1
## [5] lme4_1.1-7 Rcpp_0.11.3 Matrix_1.1-4 multcomp_1.3-7
## [9] TH.data_1.0-3 mvtnorm_0.9-9997 doBy_4.5-11 MASS_7.3-34
## [13] survival_2.37-7 latticeExtra_0.6-26 RColorBrewer_1.0-5 lattice_0.20-29
## [17] rmarkdown_0.3.3 knitr_1.7
##
## loaded via a namespace (and not attached):
## [1] digest_0.6.4 evaluate_0.5.5 formatR_1.0 htmltools_0.2.6 minqa_1.2.3
## [6] nlme_3.1-117 nloptr_1.0.4 sandwich_2.3-0 stringr_0.6.2 tools_3.1.1
## [11] yaml_2.1.13 zoo_1.7-10
trellis.device(color=FALSE)
##-----------------------------------------------------------------------------
## Leitura dos dados.
da <- read.table("http://www.leg.ufpr.br/~walmes/data/grupoexperimentos.txt",
header=TRUE, sep="\t", na.string=".")
str(da)
## 'data.frame': 300 obs. of 11 variables:
## $ local: Factor w/ 4 levels "CPAO-DDOS","MARAC",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ gen : Factor w/ 25 levels "BMX MAGNA RR",..: 15 15 15 16 16 16 25 25 25 9 ...
## $ trat : int 1 1 1 2 2 2 3 3 3 4 ...
## $ bl : int 1 2 3 1 2 3 1 2 3 1 ...
## $ df : int 34 35 35 44 44 44 36 36 36 37 ...
## $ dm : int 101 98 99 102 104 105 97 98 99 98 ...
## $ aca : num 1 2 1 1 1 1 1 1 1 1 ...
## $ ap : int 91 98 96 105 95 91 81 87 84 75 ...
## $ avag : int 13 16 15 15 12 13 14 16 14 14 ...
## $ rend : num 2444 2737 2948 2398 2579 ...
## $ p100 : num 11.2 11.3 11.2 10.2 11.2 ...
##-----------------------------------------------------------------------------
## Editar.
da <- transform(da,
bl=factor(bl),
blin=interaction(bl, local, drop=TRUE))
str(da)
## 'data.frame': 300 obs. of 12 variables:
## $ local: Factor w/ 4 levels "CPAO-DDOS","MARAC",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ gen : Factor w/ 25 levels "BMX MAGNA RR",..: 15 15 15 16 16 16 25 25 25 9 ...
## $ trat : int 1 1 1 2 2 2 3 3 3 4 ...
## $ bl : Factor w/ 3 levels "1","2","3": 1 2 3 1 2 3 1 2 3 1 ...
## $ df : int 34 35 35 44 44 44 36 36 36 37 ...
## $ dm : int 101 98 99 102 104 105 97 98 99 98 ...
## $ aca : num 1 2 1 1 1 1 1 1 1 1 ...
## $ ap : int 91 98 96 105 95 91 81 87 84 75 ...
## $ avag : int 13 16 15 15 12 13 14 16 14 14 ...
## $ rend : num 2444 2737 2948 2398 2579 ...
## $ p100 : num 11.2 11.3 11.2 10.2 11.2 ...
## $ blin : Factor w/ 12 levels "1.CPAO-DDOS",..: 1 2 3 1 2 3 1 2 3 1 ...
sum(is.na(da$rend))
## [1] 11
da <- subset(da, !is.na(rend), select=c("local","gen","blin","rend"))
str(da)
## 'data.frame': 289 obs. of 4 variables:
## $ local: Factor w/ 4 levels "CPAO-DDOS","MARAC",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ gen : Factor w/ 25 levels "BMX MAGNA RR",..: 15 15 15 16 16 25 25 25 9 9 ...
## $ blin : Factor w/ 12 levels "1.CPAO-DDOS",..: 1 2 3 1 2 1 2 3 1 2 ...
## $ rend : num 2444 2737 2948 2398 2579 ...
## Nos níveis dos fatores não pode ter nome com traço, dá problema na
## cld(). Trocar por espaço.
levels(da$gen) <- gsub("-", " ", levels(da$gen))
levels(da$local) <- gsub("-", " ", levels(da$local))
levels(da$gen)
## [1] "BMX MAGNA RR" "BMX POTÊNCIA RR" "BR 01 25656" "BR 02 04844"
## [5] "BR 02 22425" "BR 02 68661" "BR 02 72914" "BR 02 78838"
## [9] "BRS 239" "BRS 243 RR" "BRS 246 RR" "BRS 255 RR"
## [13] "BRS 268" "BRS 282" "BRS 284" "BRS 285"
## [17] "BRS 291 RR" "BRS 292 RR" "BRS 294 RR" "BRS Favorita RR"
## [21] "CD 202" "Embrapa 48" "M SOY 7908 RR" "NK 7059 RR"
## [25] "Vmax"
levels(da$local)
## [1] "CPAO DDOS" "MARAC" "NAV" "SIDROL"
##-----------------------------------------------------------------------------
## Layout.
x <- xtabs(~local+gen, data=da)
## dimnames(x) <- NULL
mosaicplot(x, off=10, las=4)
t(x)
## local
## gen CPAO DDOS MARAC NAV SIDROL
## BMX MAGNA RR 3 3 3 3
## BMX POTÊNCIA RR 3 3 3 3
## BR 01 25656 3 3 3 3
## BR 02 04844 3 2 3 3
## BR 02 22425 3 3 3 3
## BR 02 68661 3 3 3 3
## BR 02 72914 2 3 3 3
## BR 02 78838 3 3 3 3
## BRS 239 3 2 3 3
## BRS 243 RR 3 3 3 3
## BRS 246 RR 2 3 3 3
## BRS 255 RR 3 3 3 3
## BRS 268 3 3 2 3
## BRS 282 3 3 3 3
## BRS 284 3 3 2 3
## BRS 285 2 3 3 3
## BRS 291 RR 3 2 3 3
## BRS 292 RR 3 3 3 3
## BRS 294 RR 3 3 3 3
## BRS Favorita RR 3 3 3 3
## CD 202 3 3 2 3
## Embrapa 48 3 3 3 3
## M SOY 7908 RR 2 3 3 3
## NK 7059 RR 3 3 3 3
## Vmax 3 3 2 3
##-----------------------------------------------------------------------------
## Ver.
xyplot(rend~gen|local, data=da, as.table=TRUE)
##-----------------------------------------------------------------------------
## Ajuste do modelo que considera apenas o efeito de genótipo como
## fixo, os demais e interações são aleatórios.
## * fixo: gen;
## * aleatório: local, bl dentro de local e local interação com gen.
## da$y <- sqrt(da$rend)
## da$y <- log(da$rend)
da$y <- da$rend
m0 <- lmer(y~gen+(1|local)+(1|blin)+(1|local:gen),
data=da, REML=FALSE)
summary(m0)
## Linear mixed model fit by maximum likelihood ['lmerMod']
## Formula: y ~ gen + (1 | local) + (1 | blin) + (1 | local:gen)
## Data: da
##
## AIC BIC logLik deviance df.resid
## 4442.2 4548.5 -2192.1 4384.2 260
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.62640 -0.55572 -0.04777 0.56096 2.71467
##
## Random effects:
## Groups Name Variance Std.Dev.
## local:gen (Intercept) 130327 361.01
## blin (Intercept) 2330 48.27
## local (Intercept) 155226 393.99
## Residual 136231 369.09
## Number of obs: 289, groups: local:gen, 100; blin, 12; local, 4
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 3647.90 287.98 12.667
## genBMX POTÊNCIA RR 188.90 296.43 0.637
## genBR 01 25656 -25.56 296.43 -0.086
## genBR 02 04844 300.87 298.63 1.008
## genBR 02 22425 -405.27 296.43 -1.367
## genBR 02 68661 69.29 296.43 0.234
## genBR 02 72914 182.88 298.63 0.612
## genBR 02 78838 25.39 296.43 0.086
## genBRS 239 -224.91 298.63 -0.753
## genBRS 243 RR -278.74 296.43 -0.940
## genBRS 246 RR -279.82 298.63 -0.937
## genBRS 255 RR -117.83 296.43 -0.398
## genBRS 268 -334.47 298.63 -1.120
## genBRS 282 -567.89 296.43 -1.916
## genBRS 284 -124.14 298.63 -0.416
## genBRS 285 -231.22 298.63 -0.774
## genBRS 291 RR -552.31 298.63 -1.849
## genBRS 292 RR -382.38 296.43 -1.290
## genBRS 294 RR -237.63 296.43 -0.802
## genBRS Favorita RR 20.83 296.43 0.070
## genCD 202 -619.81 298.63 -2.075
## genEmbrapa 48 -539.55 296.43 -1.820
## genM SOY 7908 RR -125.79 298.63 -0.421
## genNK 7059 RR -181.84 296.43 -0.613
## genVmax -321.02 298.63 -1.075
##
## Correlation matrix not shown by default, as p = 25 > 20.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
## Abandona a interação.
m1 <- update(m0, .~.-(1|local:gen), data=da)
anova(m0, m1)
## Data: da
## Models:
## m1: y ~ gen + (1 | local) + (1 | blin)
## m0: y ~ gen + (1 | local) + (1 | blin) + (1 | local:gen)
## Df AIC BIC logLik deviance Chisq Chi Df Pr(>Chisq)
## m1 28 4497.7 4600.4 -2220.9 4441.7
## m0 29 4442.2 4548.5 -2192.1 4384.2 57.554 1 3.289e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Existe interação local:gen.
## Predição dos efeitos aleatórios.
lapply(ranef(m0), c)
## $`local:gen`
## $`local:gen`$`(Intercept)`
## [1] -12.111578 -312.990352 -100.397978 -313.796292 216.048861 103.478109 7.843113
## [8] -151.404080 106.545779 -56.593443 -119.331095 -224.648333 104.150112 466.176150
## [15] -188.230727 -246.795215 7.630458 -211.662276 -61.260587 -366.082826 282.577846
## [22] 206.646593 -256.913765 326.162441 326.883365 -137.756255 -352.994910 204.367912
## [29] 604.738880 621.788713 247.845524 742.951928 318.691933 35.043291 -166.014354
## [36] -99.038474 -267.695927 -345.010718 -250.213295 -30.507072 -313.334007 -236.467689
## [43] 264.361603 -9.197814 -147.149871 -131.381642 -400.462955 307.600739 -256.039191
## [50] -325.879159 165.535792 483.545556 353.434079 -348.748712 -597.196825 -104.512143
## [57] -656.106767 -141.670077 -132.628808 254.425978 373.046973 711.019396 -1.065030
## [64] -503.473252 -34.381493 230.395071 531.091461 158.146353 50.799564 319.029958
## [71] -769.015755 43.068370 -427.198250 81.722484 321.334097 -15.667959 182.439706
## [78] -457.404013 57.806124 -240.640749 -246.811490 -94.688274 -25.617777 -8.960262
## [85] -31.818181 -154.677404 -218.675136 241.925636 287.510397 253.119292 329.734150
## [92] -302.254230 -210.845681 19.658837 194.202738 617.819550 150.747992 376.511277
## [99] -151.845735 -322.338304
##
##
## $blin
## $blin$`(Intercept)`
## [1] 0.5277995 9.5558317 -18.4517949 -3.2469247 10.9289698 -9.8587174 -46.1611695
## [8] 6.6619318 45.9459368 0.1164028 -13.4596256 17.4413597
##
##
## $local
## $local$`(Intercept)`
## [1] -557.5040 -145.0143 429.4921 273.0262
##-----------------------------------------------------------------------------
## Teste para os termos de efeito fixo.
anova(m0)
## Analysis of Variance Table
## Df Sum Sq Mean Sq F value
## gen 24 4527370 188640 1.3847
## Não tem p-valor! É de propósito. Douglas Bates não concorda que o
## procedimento adequado para ser avaliar a estatística F seja por meio
## de ajustes no número de graus de liberdade do denominador. Para mais
## detalhes leia:
## https://stat.ethz.ch/pipermail/r-help/2006-May/094765.html
## Alternativas (em order de recomendação):
## 1. Teste de razão de verossimilhanças entre modelos aninhados (um com
## outro sem o termo fixo de interesse, usar REML=FALSE).
## 2. Teste de Wald (inferência aproximada, pacote aod).
V <- vcov(m0)
b <- fixef(m0)
nobars(formula(m0))
## y ~ gen
Terms <- which(attr(m0@pp$X, "assign")==1)
## Chi-quadrado de Wald (baseado na aproximação quadrática da
## verossimilhança).
wt <- wald.test(Sigma=V, b=b, Terms=Terms)
wt
## Wald test:
## ----------
##
## Chi-squared test:
## X2 = 33.2, df = 24, P(> X2) = 0.099
## Chi-quadrado da razão de verossimilhanças (não baseado em aproximação
## de função, melhor opção).
m1 <- update(m0, .~.-gen)
anova(m0, m1)
## Data: da
## Models:
## m1: y ~ (1 | local) + (1 | blin) + (1 | local:gen)
## m0: y ~ gen + (1 | local) + (1 | blin) + (1 | local:gen)
## Df AIC BIC logLik deviance Chisq Chi Df Pr(>Chisq)
## m1 5 4422.9 4441.3 -2206.5 4412.9
## m0 29 4442.2 4548.5 -2192.1 4384.2 28.756 24 0.2294
##-----------------------------------------------------------------------------
## Diagnóstico.
r <- residuals(m0, type="pearson")
f <- fitted(m0)
bec <- unlist(ranef(m0)[1])
beb <- unlist(ranef(m0)[2])
be <- unlist(ranef(m0)[3])
xyplot(r~f, type=c("p", "smooth"))
xyplot(sqrt(abs(r))~f, type=c("p", "smooth"))
grid.arrange(qqmath(r),
qqmath(bec),
qqmath(beb),
qqmath(be),
nrow=2)
qqmath(~r|da$local)
##-----------------------------------------------------------------------------
## Médias ajustadas.
## Formula só da parte de efeito fixo.
f <- nobars(formula(m0))
X <- LSmatrix(lm(f, da), effect=c("gen"))
rownames(X) <- levels(da$gen)
## Estimativas das médias.
summary(glht(m0, linfct=X), test=adjusted(type="none"))
##
## Simultaneous Tests for General Linear Hypotheses
##
## Fit: lmer(formula = y ~ gen + (1 | local) + (1 | blin) + (1 | local:gen),
## data = da, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## BMX MAGNA RR == 0 3647.9 288.0 12.67 <2e-16 ***
## BMX POTÊNCIA RR == 0 3836.8 288.0 13.32 <2e-16 ***
## BR 01 25656 == 0 3622.3 288.0 12.58 <2e-16 ***
## BR 02 04844 == 0 3948.8 290.3 13.61 <2e-16 ***
## BR 02 22425 == 0 3242.6 288.0 11.26 <2e-16 ***
## BR 02 68661 == 0 3717.2 288.0 12.91 <2e-16 ***
## BR 02 72914 == 0 3830.8 290.3 13.20 <2e-16 ***
## BR 02 78838 == 0 3673.3 288.0 12.76 <2e-16 ***
## BRS 239 == 0 3423.0 290.3 11.79 <2e-16 ***
## BRS 243 RR == 0 3369.2 288.0 11.70 <2e-16 ***
## BRS 246 RR == 0 3368.1 290.3 11.60 <2e-16 ***
## BRS 255 RR == 0 3530.1 288.0 12.26 <2e-16 ***
## BRS 268 == 0 3313.4 290.3 11.42 <2e-16 ***
## BRS 282 == 0 3080.0 288.0 10.70 <2e-16 ***
## BRS 284 == 0 3523.8 290.3 12.14 <2e-16 ***
## BRS 285 == 0 3416.7 290.3 11.77 <2e-16 ***
## BRS 291 RR == 0 3095.6 290.3 10.66 <2e-16 ***
## BRS 292 RR == 0 3265.5 288.0 11.34 <2e-16 ***
## BRS 294 RR == 0 3410.3 288.0 11.84 <2e-16 ***
## BRS Favorita RR == 0 3668.7 288.0 12.74 <2e-16 ***
## CD 202 == 0 3028.1 290.3 10.43 <2e-16 ***
## Embrapa 48 == 0 3108.3 288.0 10.79 <2e-16 ***
## M SOY 7908 RR == 0 3522.1 290.3 12.13 <2e-16 ***
## NK 7059 RR == 0 3466.1 288.0 12.04 <2e-16 ***
## Vmax == 0 3326.9 290.3 11.46 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- none method)
## Contraste.
Xc <- apc(X)
dim(Xc)
## [1] 300 25
g <- summary(glht(m0, linfct=Xc), test=adjusted(type="fdr")); g
##
## Simultaneous Tests for General Linear Hypotheses
##
## Fit: lmer(formula = y ~ gen + (1 | local) + (1 | blin) + (1 | local:gen),
## data = da, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## BMX MAGNA RR-BMX POTÊNCIA RR == 0 -188.898 296.426 -0.637 0.832
## BMX MAGNA RR-BR 01 25656 == 0 25.562 296.426 0.086 0.977
## BMX MAGNA RR-BR 02 04844 == 0 -300.872 298.632 -1.008 0.725
## BMX MAGNA RR-BR 02 22425 == 0 405.272 296.426 1.367 0.630
## BMX MAGNA RR-BR 02 68661 == 0 -69.288 296.426 -0.234 0.944
## BMX MAGNA RR-BR 02 72914 == 0 -182.877 298.632 -0.612 0.840
## BMX MAGNA RR-BR 02 78838 == 0 -25.387 296.426 -0.086 0.977
## BMX MAGNA RR-BRS 239 == 0 224.908 298.632 0.753 0.806
## BMX MAGNA RR-BRS 243 RR == 0 278.736 296.426 0.940 0.738
## BMX MAGNA RR-BRS 246 RR == 0 279.815 298.632 0.937 0.738
## BMX MAGNA RR-BRS 255 RR == 0 117.835 296.426 0.398 0.892
## BMX MAGNA RR-BRS 268 == 0 334.474 298.632 1.120 0.725
## BMX MAGNA RR-BRS 282 == 0 567.886 296.426 1.916 0.476
## BMX MAGNA RR-BRS 284 == 0 124.142 298.633 0.416 0.892
## BMX MAGNA RR-BRS 285 == 0 231.222 298.632 0.774 0.798
## BMX MAGNA RR-BRS 291 RR == 0 552.311 298.632 1.849 0.508
## BMX MAGNA RR-BRS 292 RR == 0 382.376 296.426 1.290 0.661
## BMX MAGNA RR-BRS 294 RR == 0 237.626 296.426 0.802 0.788
## BMX MAGNA RR-BRS Favorita RR == 0 -20.830 296.426 -0.070 0.983
## BMX MAGNA RR-CD 202 == 0 619.806 298.633 2.075 0.476
## BMX MAGNA RR-Embrapa 48 == 0 539.554 296.426 1.820 0.515
## BMX MAGNA RR-M SOY 7908 RR == 0 125.791 298.632 0.421 0.892
## BMX MAGNA RR-NK 7059 RR == 0 181.837 296.426 0.613 0.840
## BMX MAGNA RR-Vmax == 0 321.022 298.633 1.075 0.725
## BMX POTÊNCIA RR-BR 01 25656 == 0 214.460 296.426 0.723 0.818
## BMX POTÊNCIA RR-BR 02 04844 == 0 -111.973 298.632 -0.375 0.892
## BMX POTÊNCIA RR-BR 02 22425 == 0 594.171 296.426 2.004 0.476
## BMX POTÊNCIA RR-BR 02 68661 == 0 119.610 296.426 0.404 0.892
## BMX POTÊNCIA RR-BR 02 72914 == 0 6.021 298.632 0.020 0.994
## BMX POTÊNCIA RR-BR 02 78838 == 0 163.512 296.426 0.552 0.858
## BMX POTÊNCIA RR-BRS 239 == 0 413.807 298.632 1.386 0.630
## BMX POTÊNCIA RR-BRS 243 RR == 0 467.634 296.426 1.578 0.624
## BMX POTÊNCIA RR-BRS 246 RR == 0 468.713 298.632 1.570 0.624
## BMX POTÊNCIA RR-BRS 255 RR == 0 306.733 296.426 1.035 0.725
## BMX POTÊNCIA RR-BRS 268 == 0 523.373 298.632 1.753 0.537
## BMX POTÊNCIA RR-BRS 282 == 0 756.784 296.426 2.553 0.389
## BMX POTÊNCIA RR-BRS 284 == 0 313.040 298.633 1.048 0.725
## BMX POTÊNCIA RR-BRS 285 == 0 420.120 298.632 1.407 0.630
## BMX POTÊNCIA RR-BRS 291 RR == 0 741.209 298.632 2.482 0.389
## BMX POTÊNCIA RR-BRS 292 RR == 0 571.274 296.426 1.927 0.476
## BMX POTÊNCIA RR-BRS 294 RR == 0 426.524 296.426 1.439 0.630
## BMX POTÊNCIA RR-BRS Favorita RR == 0 168.068 296.426 0.567 0.858
## BMX POTÊNCIA RR-CD 202 == 0 808.704 298.633 2.708 0.381
## BMX POTÊNCIA RR-Embrapa 48 == 0 728.452 296.426 2.457 0.389
## BMX POTÊNCIA RR-M SOY 7908 RR == 0 314.689 298.632 1.054 0.725
## BMX POTÊNCIA RR-NK 7059 RR == 0 370.735 296.426 1.251 0.688
## BMX POTÊNCIA RR-Vmax == 0 509.920 298.633 1.708 0.548
## BR 01 25656-BR 02 04844 == 0 -326.433 298.632 -1.093 0.725
## BR 01 25656-BR 02 22425 == 0 379.711 296.426 1.281 0.661
## BR 01 25656-BR 02 68661 == 0 -94.850 296.426 -0.320 0.892
## BR 01 25656-BR 02 72914 == 0 -208.439 298.632 -0.698 0.818
## BR 01 25656-BR 02 78838 == 0 -50.948 296.426 -0.172 0.945
## BR 01 25656-BRS 239 == 0 199.347 298.632 0.668 0.822
## BR 01 25656-BRS 243 RR == 0 253.174 296.426 0.854 0.762
## BR 01 25656-BRS 246 RR == 0 254.253 298.632 0.851 0.762
## BR 01 25656-BRS 255 RR == 0 92.273 296.426 0.311 0.896
## BR 01 25656-BRS 268 == 0 308.913 298.632 1.034 0.725
## BR 01 25656-BRS 282 == 0 542.324 296.426 1.830 0.515
## BR 01 25656-BRS 284 == 0 98.580 298.633 0.330 0.892
## BR 01 25656-BRS 285 == 0 205.660 298.632 0.689 0.818
## BR 01 25656-BRS 291 RR == 0 526.749 298.632 1.764 0.537
## BR 01 25656-BRS 292 RR == 0 356.814 296.426 1.204 0.707
## BR 01 25656-BRS 294 RR == 0 212.064 296.426 0.715 0.818
## BR 01 25656-BRS Favorita RR == 0 -46.392 296.426 -0.157 0.945
## BR 01 25656-CD 202 == 0 594.244 298.633 1.990 0.476
## BR 01 25656-Embrapa 48 == 0 513.992 296.426 1.734 0.541
## BR 01 25656-M SOY 7908 RR == 0 100.229 298.632 0.336 0.892
## BR 01 25656-NK 7059 RR == 0 156.275 296.426 0.527 0.858
## BR 01 25656-Vmax == 0 295.460 298.633 0.989 0.732
## BR 02 04844-BR 02 22425 == 0 706.144 298.632 2.365 0.417
## BR 02 04844-BR 02 68661 == 0 231.583 298.632 0.775 0.798
## BR 02 04844-BR 02 72914 == 0 117.995 300.827 0.392 0.892
## BR 02 04844-BR 02 78838 == 0 275.485 298.632 0.922 0.747
## BR 02 04844-BRS 239 == 0 525.780 300.831 1.748 0.537
## BR 02 04844-BRS 243 RR == 0 579.608 298.632 1.941 0.476
## BR 02 04844-BRS 246 RR == 0 580.687 300.827 1.930 0.476
## BR 02 04844-BRS 255 RR == 0 418.707 298.632 1.402 0.630
## BR 02 04844-BRS 268 == 0 635.346 300.826 2.112 0.476
## BR 02 04844-BRS 282 == 0 868.758 298.632 2.909 0.367
## BR 02 04844-BRS 284 == 0 425.013 300.827 1.413 0.630
## BR 02 04844-BRS 285 == 0 532.094 300.827 1.769 0.537
## BR 02 04844-BRS 291 RR == 0 853.183 300.831 2.836 0.367
## BR 02 04844-BRS 292 RR == 0 683.248 298.632 2.288 0.443
## BR 02 04844-BRS 294 RR == 0 538.498 298.632 1.803 0.522
## BR 02 04844-BRS Favorita RR == 0 280.042 298.632 0.938 0.738
## BR 02 04844-CD 202 == 0 920.677 300.827 3.060 0.367
## BR 02 04844-Embrapa 48 == 0 840.426 298.632 2.814 0.367
## BR 02 04844-M SOY 7908 RR == 0 426.663 300.827 1.418 0.630
## BR 02 04844-NK 7059 RR == 0 482.708 298.632 1.616 0.600
## BR 02 04844-Vmax == 0 621.894 300.827 2.067 0.476
## BR 02 22425-BR 02 68661 == 0 -474.561 296.426 -1.601 0.608
## BR 02 22425-BR 02 72914 == 0 -588.149 298.632 -1.969 0.476
## BR 02 22425-BR 02 78838 == 0 -430.659 296.426 -1.453 0.630
## BR 02 22425-BRS 239 == 0 -180.364 298.632 -0.604 0.844
## BR 02 22425-BRS 243 RR == 0 -126.537 296.426 -0.427 0.892
## BR 02 22425-BRS 246 RR == 0 -125.457 298.632 -0.420 0.892
## BR 02 22425-BRS 255 RR == 0 -287.438 296.426 -0.970 0.738
## BR 02 22425-BRS 268 == 0 -70.798 298.632 -0.237 0.944
## BR 02 22425-BRS 282 == 0 162.613 296.426 0.549 0.858
## BR 02 22425-BRS 284 == 0 -281.131 298.633 -0.941 0.738
## BR 02 22425-BRS 285 == 0 -174.051 298.632 -0.583 0.858
## BR 02 22425-BRS 291 RR == 0 147.038 298.632 0.492 0.858
## BR 02 22425-BRS 292 RR == 0 -22.897 296.426 -0.077 0.981
## BR 02 22425-BRS 294 RR == 0 -167.647 296.426 -0.566 0.858
## BR 02 22425-BRS Favorita RR == 0 -426.102 296.426 -1.437 0.630
## BR 02 22425-CD 202 == 0 214.533 298.633 0.718 0.818
## BR 02 22425-Embrapa 48 == 0 134.282 296.426 0.453 0.875
## BR 02 22425-M SOY 7908 RR == 0 -279.482 298.632 -0.936 0.738
## BR 02 22425-NK 7059 RR == 0 -223.436 296.426 -0.754 0.806
## BR 02 22425-Vmax == 0 -84.250 298.633 -0.282 0.914
## BR 02 68661-BR 02 72914 == 0 -113.589 298.632 -0.380 0.892
## BR 02 68661-BR 02 78838 == 0 43.902 296.426 0.148 0.945
## BR 02 68661-BRS 239 == 0 294.197 298.632 0.985 0.732
## BR 02 68661-BRS 243 RR == 0 348.024 296.426 1.174 0.725
## BR 02 68661-BRS 246 RR == 0 349.103 298.632 1.169 0.725
## BR 02 68661-BRS 255 RR == 0 187.123 296.426 0.631 0.833
## BR 02 68661-BRS 268 == 0 403.763 298.632 1.352 0.630
## BR 02 68661-BRS 282 == 0 637.174 296.426 2.150 0.476
## BR 02 68661-BRS 284 == 0 193.430 298.633 0.648 0.825
## BR 02 68661-BRS 285 == 0 300.510 298.632 1.006 0.725
## BR 02 68661-BRS 291 RR == 0 621.599 298.632 2.081 0.476
## BR 02 68661-BRS 292 RR == 0 451.664 296.426 1.524 0.630
## BR 02 68661-BRS 294 RR == 0 306.914 296.426 1.035 0.725
## BR 02 68661-BRS Favorita RR == 0 48.458 296.426 0.163 0.945
## BR 02 68661-CD 202 == 0 689.094 298.633 2.307 0.443
## BR 02 68661-Embrapa 48 == 0 608.842 296.426 2.054 0.476
## BR 02 68661-M SOY 7908 RR == 0 195.079 298.632 0.653 0.825
## BR 02 68661-NK 7059 RR == 0 251.125 296.426 0.847 0.762
## BR 02 68661-Vmax == 0 390.310 298.633 1.307 0.661
## BR 02 72914-BR 02 78838 == 0 157.490 298.632 0.527 0.858
## BR 02 72914-BRS 239 == 0 407.785 300.827 1.356 0.630
## BR 02 72914-BRS 243 RR == 0 461.613 298.632 1.546 0.630
## BR 02 72914-BRS 246 RR == 0 462.692 300.832 1.538 0.630
## BR 02 72914-BRS 255 RR == 0 300.712 298.632 1.007 0.725
## BR 02 72914-BRS 268 == 0 517.351 300.827 1.720 0.546
## BR 02 72914-BRS 282 == 0 750.763 298.632 2.514 0.389
## BR 02 72914-BRS 284 == 0 307.019 300.828 1.021 0.725
## BR 02 72914-BRS 285 == 0 414.099 300.832 1.377 0.630
## BR 02 72914-BRS 291 RR == 0 735.188 300.827 2.444 0.389
## BR 02 72914-BRS 292 RR == 0 565.253 298.632 1.893 0.476
## BR 02 72914-BRS 294 RR == 0 420.503 298.632 1.408 0.630
## BR 02 72914-BRS Favorita RR == 0 162.047 298.632 0.543 0.858
## BR 02 72914-CD 202 == 0 802.683 300.828 2.668 0.381
## BR 02 72914-Embrapa 48 == 0 722.431 298.632 2.419 0.389
## BR 02 72914-M SOY 7908 RR == 0 308.668 300.759 1.026 0.725
## BR 02 72914-NK 7059 RR == 0 364.714 298.632 1.221 0.707
## BR 02 72914-Vmax == 0 503.899 300.828 1.675 0.564
## BR 02 78838-BRS 239 == 0 250.295 298.632 0.838 0.763
## BR 02 78838-BRS 243 RR == 0 304.122 296.426 1.026 0.725
## BR 02 78838-BRS 246 RR == 0 305.202 298.632 1.022 0.725
## BR 02 78838-BRS 255 RR == 0 143.222 296.426 0.483 0.858
## BR 02 78838-BRS 268 == 0 359.861 298.632 1.205 0.707
## BR 02 78838-BRS 282 == 0 593.272 296.426 2.001 0.476
## BR 02 78838-BRS 284 == 0 149.528 298.633 0.501 0.858
## BR 02 78838-BRS 285 == 0 256.608 298.632 0.859 0.762
## BR 02 78838-BRS 291 RR == 0 577.697 298.632 1.934 0.476
## BR 02 78838-BRS 292 RR == 0 407.762 296.426 1.376 0.630
## BR 02 78838-BRS 294 RR == 0 263.012 296.426 0.887 0.762
## BR 02 78838-BRS Favorita RR == 0 4.557 296.426 0.015 0.994
## BR 02 78838-CD 202 == 0 645.192 298.633 2.160 0.476
## BR 02 78838-Embrapa 48 == 0 564.941 296.426 1.906 0.476
## BR 02 78838-M SOY 7908 RR == 0 151.178 298.632 0.506 0.858
## BR 02 78838-NK 7059 RR == 0 207.223 296.426 0.699 0.818
## BR 02 78838-Vmax == 0 346.409 298.633 1.160 0.725
## BRS 239-BRS 243 RR == 0 53.828 298.632 0.180 0.945
## BRS 239-BRS 246 RR == 0 54.907 300.827 0.183 0.945
## BRS 239-BRS 255 RR == 0 -107.073 298.632 -0.359 0.892
## BRS 239-BRS 268 == 0 109.566 300.826 0.364 0.892
## BRS 239-BRS 282 == 0 342.978 298.632 1.148 0.725
## BRS 239-BRS 284 == 0 -100.766 300.827 -0.335 0.892
## BRS 239-BRS 285 == 0 6.314 300.827 0.021 0.994
## BRS 239-BRS 291 RR == 0 327.403 300.831 1.088 0.725
## BRS 239-BRS 292 RR == 0 157.468 298.632 0.527 0.858
## BRS 239-BRS 294 RR == 0 12.718 298.632 0.043 0.992
## BRS 239-BRS Favorita RR == 0 -245.738 298.632 -0.823 0.770
## BRS 239-CD 202 == 0 394.898 300.827 1.313 0.661
## BRS 239-Embrapa 48 == 0 314.646 298.632 1.054 0.725
## BRS 239-M SOY 7908 RR == 0 -99.117 300.827 -0.329 0.892
## BRS 239-NK 7059 RR == 0 -43.072 298.632 -0.144 0.945
## BRS 239-Vmax == 0 96.114 300.827 0.319 0.892
## BRS 243 RR-BRS 246 RR == 0 1.079 298.632 0.004 0.997
## BRS 243 RR-BRS 255 RR == 0 -160.901 296.426 -0.543 0.858
## BRS 243 RR-BRS 268 == 0 55.739 298.632 0.187 0.945
## BRS 243 RR-BRS 282 == 0 289.150 296.426 0.975 0.737
## BRS 243 RR-BRS 284 == 0 -154.594 298.633 -0.518 0.858
## BRS 243 RR-BRS 285 == 0 -47.514 298.632 -0.159 0.945
## BRS 243 RR-BRS 291 RR == 0 273.575 298.632 0.916 0.749
## BRS 243 RR-BRS 292 RR == 0 103.640 296.426 0.350 0.892
## BRS 243 RR-BRS 294 RR == 0 -41.110 296.426 -0.139 0.945
## BRS 243 RR-BRS Favorita RR == 0 -299.566 296.426 -1.011 0.725
## BRS 243 RR-CD 202 == 0 341.070 298.633 1.142 0.725
## BRS 243 RR-Embrapa 48 == 0 260.818 296.426 0.880 0.762
## BRS 243 RR-M SOY 7908 RR == 0 -152.945 298.632 -0.512 0.858
## BRS 243 RR-NK 7059 RR == 0 -96.899 296.426 -0.327 0.892
## BRS 243 RR-Vmax == 0 42.286 298.633 0.142 0.945
## BRS 246 RR-BRS 255 RR == 0 -161.980 298.632 -0.542 0.858
## BRS 246 RR-BRS 268 == 0 54.659 300.827 0.182 0.945
## BRS 246 RR-BRS 282 == 0 288.071 298.632 0.965 0.738
## BRS 246 RR-BRS 284 == 0 -155.673 300.828 -0.517 0.858
## BRS 246 RR-BRS 285 == 0 -48.593 300.759 -0.162 0.945
## BRS 246 RR-BRS 291 RR == 0 272.496 300.827 0.906 0.755
## BRS 246 RR-BRS 292 RR == 0 102.561 298.632 0.343 0.892
## BRS 246 RR-BRS 294 RR == 0 -42.189 298.632 -0.141 0.945
## BRS 246 RR-BRS Favorita RR == 0 -300.645 298.632 -1.007 0.725
## BRS 246 RR-CD 202 == 0 339.991 300.828 1.130 0.725
## BRS 246 RR-Embrapa 48 == 0 259.739 298.632 0.870 0.762
## BRS 246 RR-M SOY 7908 RR == 0 -154.024 300.832 -0.512 0.858
## BRS 246 RR-NK 7059 RR == 0 -97.978 298.632 -0.328 0.892
## BRS 246 RR-Vmax == 0 41.207 300.828 0.137 0.945
## BRS 255 RR-BRS 268 == 0 216.639 298.632 0.725 0.818
## BRS 255 RR-BRS 282 == 0 450.051 296.426 1.518 0.630
## BRS 255 RR-BRS 284 == 0 6.307 298.633 0.021 0.994
## BRS 255 RR-BRS 285 == 0 113.387 298.632 0.380 0.892
## BRS 255 RR-BRS 291 RR == 0 434.476 298.632 1.455 0.630
## BRS 255 RR-BRS 292 RR == 0 264.541 296.426 0.892 0.762
## BRS 255 RR-BRS 294 RR == 0 119.791 296.426 0.404 0.892
## BRS 255 RR-BRS Favorita RR == 0 -138.665 296.426 -0.468 0.866
## BRS 255 RR-CD 202 == 0 501.971 298.633 1.681 0.564
## BRS 255 RR-Embrapa 48 == 0 421.719 296.426 1.423 0.630
## BRS 255 RR-M SOY 7908 RR == 0 7.956 298.632 0.027 0.994
## BRS 255 RR-NK 7059 RR == 0 64.002 296.426 0.216 0.945
## BRS 255 RR-Vmax == 0 203.187 298.633 0.680 0.818
## BRS 268-BRS 282 == 0 233.411 298.632 0.782 0.798
## BRS 268-BRS 284 == 0 -210.333 300.832 -0.699 0.818
## BRS 268-BRS 285 == 0 -103.253 300.827 -0.343 0.892
## BRS 268-BRS 291 RR == 0 217.836 300.826 0.724 0.818
## BRS 268-BRS 292 RR == 0 47.901 298.632 0.160 0.945
## BRS 268-BRS 294 RR == 0 -96.849 298.632 -0.324 0.892
## BRS 268-BRS Favorita RR == 0 -355.304 298.632 -1.190 0.717
## BRS 268-CD 202 == 0 285.331 300.832 0.948 0.738
## BRS 268-Embrapa 48 == 0 205.080 298.632 0.687 0.818
## BRS 268-M SOY 7908 RR == 0 -208.684 300.827 -0.694 0.818
## BRS 268-NK 7059 RR == 0 -152.638 298.632 -0.511 0.858
## BRS 268-Vmax == 0 -13.452 300.832 -0.045 0.992
## BRS 282-BRS 284 == 0 -443.744 298.633 -1.486 0.630
## BRS 282-BRS 285 == 0 -336.664 298.632 -1.127 0.725
## BRS 282-BRS 291 RR == 0 -15.575 298.632 -0.052 0.992
## BRS 282-BRS 292 RR == 0 -185.510 296.426 -0.626 0.835
## BRS 282-BRS 294 RR == 0 -330.260 296.426 -1.114 0.725
## BRS 282-BRS Favorita RR == 0 -588.716 296.426 -1.986 0.476
## BRS 282-CD 202 == 0 51.920 298.633 0.174 0.945
## BRS 282-Embrapa 48 == 0 -28.332 296.426 -0.096 0.976
## BRS 282-M SOY 7908 RR == 0 -442.095 298.632 -1.480 0.630
## BRS 282-NK 7059 RR == 0 -386.049 296.426 -1.302 0.661
## BRS 282-Vmax == 0 -246.864 298.633 -0.827 0.770
## BRS 284-BRS 285 == 0 107.080 300.828 0.356 0.892
## BRS 284-BRS 291 RR == 0 428.169 300.827 1.423 0.630
## BRS 284-BRS 292 RR == 0 258.234 298.633 0.865 0.762
## BRS 284-BRS 294 RR == 0 113.484 298.633 0.380 0.892
## BRS 284-BRS Favorita RR == 0 -144.972 298.633 -0.485 0.858
## BRS 284-CD 202 == 0 495.664 300.759 1.648 0.580
## BRS 284-Embrapa 48 == 0 415.412 298.633 1.391 0.630
## BRS 284-M SOY 7908 RR == 0 1.649 300.828 0.005 0.997
## BRS 284-NK 7059 RR == 0 57.695 298.633 0.193 0.945
## BRS 284-Vmax == 0 196.880 300.759 0.655 0.825
## BRS 285-BRS 291 RR == 0 321.089 300.827 1.067 0.725
## BRS 285-BRS 292 RR == 0 151.154 298.632 0.506 0.858
## BRS 285-BRS 294 RR == 0 6.404 298.632 0.021 0.994
## BRS 285-BRS Favorita RR == 0 -252.052 298.632 -0.844 0.762
## BRS 285-CD 202 == 0 388.584 300.828 1.292 0.661
## BRS 285-Embrapa 48 == 0 308.332 298.632 1.032 0.725
## BRS 285-M SOY 7908 RR == 0 -105.431 300.832 -0.350 0.892
## BRS 285-NK 7059 RR == 0 -49.385 298.632 -0.165 0.945
## BRS 285-Vmax == 0 89.800 300.828 0.299 0.904
## BRS 291 RR-BRS 292 RR == 0 -169.935 298.632 -0.569 0.858
## BRS 291 RR-BRS 294 RR == 0 -314.685 298.632 -1.054 0.725
## BRS 291 RR-BRS Favorita RR == 0 -573.141 298.632 -1.919 0.476
## BRS 291 RR-CD 202 == 0 67.495 300.827 0.224 0.945
## BRS 291 RR-Embrapa 48 == 0 -12.757 298.632 -0.043 0.992
## BRS 291 RR-M SOY 7908 RR == 0 -426.520 300.827 -1.418 0.630
## BRS 291 RR-NK 7059 RR == 0 -370.474 298.632 -1.241 0.693
## BRS 291 RR-Vmax == 0 -231.289 300.827 -0.769 0.799
## BRS 292 RR-BRS 294 RR == 0 -144.750 296.426 -0.488 0.858
## BRS 292 RR-BRS Favorita RR == 0 -403.206 296.426 -1.360 0.630
## BRS 292 RR-CD 202 == 0 237.430 298.633 0.795 0.790
## BRS 292 RR-Embrapa 48 == 0 157.178 296.426 0.530 0.858
## BRS 292 RR-M SOY 7908 RR == 0 -256.585 298.632 -0.859 0.762
## BRS 292 RR-NK 7059 RR == 0 -200.539 296.426 -0.677 0.818
## BRS 292 RR-Vmax == 0 -61.354 298.633 -0.205 0.945
## BRS 294 RR-BRS Favorita RR == 0 -258.456 296.426 -0.872 0.762
## BRS 294 RR-CD 202 == 0 382.180 298.633 1.280 0.661
## BRS 294 RR-Embrapa 48 == 0 301.928 296.426 1.019 0.725
## BRS 294 RR-M SOY 7908 RR == 0 -111.835 298.632 -0.374 0.892
## BRS 294 RR-NK 7059 RR == 0 -55.789 296.426 -0.188 0.945
## BRS 294 RR-Vmax == 0 83.396 298.633 0.279 0.914
## BRS Favorita RR-CD 202 == 0 640.636 298.633 2.145 0.476
## BRS Favorita RR-Embrapa 48 == 0 560.384 296.426 1.890 0.476
## BRS Favorita RR-M SOY 7908 RR == 0 146.621 298.632 0.491 0.858
## BRS Favorita RR-NK 7059 RR == 0 202.667 296.426 0.684 0.818
## BRS Favorita RR-Vmax == 0 341.852 298.633 1.145 0.725
## CD 202-Embrapa 48 == 0 -80.252 298.633 -0.269 0.920
## CD 202-M SOY 7908 RR == 0 -494.015 300.828 -1.642 0.580
## CD 202-NK 7059 RR == 0 -437.969 298.633 -1.467 0.630
## CD 202-Vmax == 0 -298.784 300.759 -0.993 0.732
## Embrapa 48-M SOY 7908 RR == 0 -413.763 298.632 -1.386 0.630
## Embrapa 48-NK 7059 RR == 0 -357.718 296.426 -1.207 0.707
## Embrapa 48-Vmax == 0 -218.532 298.633 -0.732 0.818
## M SOY 7908 RR-NK 7059 RR == 0 56.046 298.632 0.188 0.945
## M SOY 7908 RR-Vmax == 0 195.231 300.828 0.649 0.825
## NK 7059 RR-Vmax == 0 139.185 298.633 0.466 0.866
## (Adjusted p values reported -- fdr method)
## Estimativas das médias com comparações.
## grid <- apmc(X=X, model=m0, focus="gen", test="bonferroni")
grid <- apmc(X=X, model=m0, focus="gen", test="fdr")
grid
## gen estimate lwr upr cld
## 1 BMX MAGNA RR 3647.902 3083.463 4212.341 a
## 2 BMX POTÊNCIA RR 3836.800 3272.361 4401.239 a
## 3 BR 01 25656 3622.340 3057.901 4186.779 a
## 4 BR 02 04844 3948.773 3379.885 4517.661 a
## 5 BR 02 22425 3242.629 2678.190 3807.068 a
## 6 BR 02 68661 3717.190 3152.751 4281.629 a
## 7 BR 02 72914 3830.779 3261.890 4399.668 a
## 8 BR 02 78838 3673.288 3108.849 4237.727 a
## 9 BRS 239 3422.993 2854.105 3991.881 a
## 10 BRS 243 RR 3369.166 2804.727 3933.605 a
## 11 BRS 246 RR 3368.087 2799.198 3936.976 a
## 12 BRS 255 RR 3530.067 2965.628 4094.506 a
## 13 BRS 268 3313.427 2744.539 3882.315 a
## 14 BRS 282 3080.016 2515.577 3644.455 a
## 15 BRS 284 3523.760 2954.870 4092.650 a
## 16 BRS 285 3416.680 2847.791 3985.569 a
## 17 BRS 291 RR 3095.591 2526.703 3664.479 a
## 18 BRS 292 RR 3265.526 2701.087 3829.965 a
## 19 BRS 294 RR 3410.276 2845.837 3974.715 a
## 20 BRS Favorita RR 3668.732 3104.293 4233.171 a
## 21 CD 202 3028.096 2459.206 3596.986 a
## 22 Embrapa 48 3108.348 2543.908 3672.787 a
## 23 M SOY 7908 RR 3522.111 2953.222 4091.000 a
## 24 NK 7059 RR 3466.065 2901.626 4030.504 a
## 25 Vmax 3326.880 2757.990 3895.769 a
##-----------------------------------------------------------------------------
## Gráfico.
segplot(reorder(gen, estimate)~lwr+upr, centers=estimate,
ylab="Cultivar de soja", xlab="Produtividade",
data=grid, draw=FALSE, cld=grid$cld,
panel=function(x, y, z, centers, subscripts, cld, ...){
panel.segplot(x, y, z, centers=centers,
subscripts=subscripts, ...)
panel.text(x=centers[subscripts], y=as.numeric(z)[subscripts],
labels=cld[subscripts], pos=4)
})
##-----------------------------------------------------------------------------
## Para desdobrar a interação local:gen, tratar como efeito fixo.
formula(m0)
## y ~ gen + (1 | local) + (1 | blin) + (1 | local:gen)
m0 <- lmer(y~local*gen+(1|blin),
data=da, REML=FALSE)
##-----------------------------------------------------------------------------
## Fazer o desdobramento dentro do primeiro local. Os demais seguem a
## mesma regra.
X <- LSmatrix(lm(nobars(formula(m0)), data=da), effect=c("local","gen"))
dim(X)
## [1] 100 100
L <- by(X, attr(X, "grid")$local, as.matrix)
L <- lapply(L, "rownames<-", levels(da$gen))
str(L)
## List of 4
## $ CPAO DDOS: num [1:25, 1:100] 1 1 1 1 1 1 1 1 1 1 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ : chr [1:25] "BMX MAGNA RR" "BMX POTÊNCIA RR" "BR 01 25656" "BR 02 04844" ...
## .. ..$ : chr [1:100] "(Intercept)" "localMARAC" "localNAV" "localSIDROL" ...
## $ MARAC : num [1:25, 1:100] 1 1 1 1 1 1 1 1 1 1 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ : chr [1:25] "BMX MAGNA RR" "BMX POTÊNCIA RR" "BR 01 25656" "BR 02 04844" ...
## .. ..$ : chr [1:100] "(Intercept)" "localMARAC" "localNAV" "localSIDROL" ...
## $ NAV : num [1:25, 1:100] 1 1 1 1 1 1 1 1 1 1 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ : chr [1:25] "BMX MAGNA RR" "BMX POTÊNCIA RR" "BR 01 25656" "BR 02 04844" ...
## .. ..$ : chr [1:100] "(Intercept)" "localMARAC" "localNAV" "localSIDROL" ...
## $ SIDROL : num [1:25, 1:100] 1 1 1 1 1 1 1 1 1 1 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ : chr [1:25] "BMX MAGNA RR" "BMX POTÊNCIA RR" "BR 01 25656" "BR 02 04844" ...
## .. ..$ : chr [1:100] "(Intercept)" "localMARAC" "localNAV" "localSIDROL" ...
grid <- lapply(L, apmc, model=m0, focus="gen", test="fdr")
str(grid)
## List of 4
## $ CPAO DDOS:'data.frame': 25 obs. of 5 variables:
## ..$ gen : Factor w/ 25 levels "BMX MAGNA RR",..: 1 2 3 4 5 6 7 8 9 10 ...
## ..$ estimate: num [1:25] 3071 2854 2927 2965 2974 ...
## ..$ lwr : num [1:25] 2731 2514 2586 2625 2633 ...
## ..$ upr : num [1:25] 3412 3195 3267 3306 3314 ...
## ..$ cld : chr [1:25] "ab" "ab" "ab" "ab" ...
## $ MARAC :'data.frame': 25 obs. of 5 variables:
## ..$ gen : Factor w/ 25 levels "BMX MAGNA RR",..: 1 2 3 4 5 6 7 8 9 10 ...
## ..$ estimate: num [1:25] 3316 3215 3752 4725 3935 ...
## ..$ lwr : num [1:25] 2976 2875 3412 4309 3595 ...
## ..$ upr : num [1:25] 3657 3556 4093 5142 4276 ...
## ..$ cld : chr [1:25] "cef" "efgi" "cdh" "a" ...
## $ NAV :'data.frame': 25 obs. of 5 variables:
## ..$ gen : Factor w/ 25 levels "BMX MAGNA RR",..: 1 2 3 4 5 6 7 8 9 10 ...
## ..$ estimate: num [1:25] 4303 4920 4531 3910 2869 ...
## ..$ lwr : num [1:25] 3962 4580 4190 3570 2529 ...
## ..$ upr : num [1:25] 4643 5261 4871 4251 3209 ...
## ..$ cld : chr [1:25] "cd" "a" "ac" "bdf" ...
## $ SIDROL :'data.frame': 25 obs. of 5 variables:
## ..$ gen : Factor w/ 25 levels "BMX MAGNA RR",..: 1 2 3 4 5 6 7 8 9 10 ...
## ..$ estimate: num [1:25] 3901 4357 3280 4301 3193 ...
## ..$ lwr : num [1:25] 3561 4017 2939 3961 2852 ...
## ..$ upr : num [1:25] 4242 4698 3620 4642 3533 ...
## ..$ cld : chr [1:25] "dfg" "f" "ac" "bf" ...
grid <- ldply(grid); names(grid)[1] <- "local"
grid <- equallevels(grid, da)
str(grid)
## 'data.frame': 100 obs. of 6 variables:
## $ local : Factor w/ 4 levels "CPAO DDOS","MARAC",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ gen : Factor w/ 25 levels "BMX MAGNA RR",..: 1 2 3 4 5 6 7 8 9 10 ...
## $ estimate: num 3071 2854 2927 2965 2974 ...
## $ lwr : num 2731 2514 2586 2625 2633 ...
## $ upr : num 3412 3195 3267 3306 3314 ...
## $ cld : chr "ab" "ab" "ab" "ab" ...
##-----------------------------------------------------------------------------
## Gráfico.
segplot(gen~lwr+upr|local, centers=estimate,
ylab="Genivar de arroz", xlab="Produtividade",
data=grid, draw=FALSE, strip=FALSE, strip.left=TRUE,
scales=list(
y=list(relation="free", rot=0)),
layout=c(2,NA))
##-----------------------------------------------------------------------------
## Truque para ordenar gen dentro dos locais no gráfico.
## Função que remove o texto antes do ponto separador.
yscale.components.dropend <- function(...){
ans <- yscale.components.default(...)
lab <- ans$left$labels$labels
ans$left$labels$labels <- gsub("^.*\\.", "", lab)
ans
}
## Número de gen em cada local.
ngen <- apply(xtabs(~local+gen, da), 1, function(i) sum(i>0))
ngen
## CPAO DDOS MARAC NAV SIDROL
## 25 25 25 25
grid$locgen <- with(grid, interaction(local, gen))
## Ordem original dos níveis do fator locgen.
on <- levels(grid$locgen)
neworder <- with(grid, order(local, estimate))
orderin <- by(grid, INDICE=grid$local,
function(i){
as.character(i$locgen[order(i$estimate)])
})
## Uma cópia do fator com ondem diferente dos níveis.
grid$locgen2 <- factor(grid$locgen, levels=unlist(orderin))
segplot(locgen2~lwr+upr|local, centers=estimate,
ylab="Cultivar de soja", xlab="Produtividade",
data=grid, draw=FALSE,
scales=list(y=list(relation="free", rot=0, tck=0.5, cex=0.7)),
yscale.components=yscale.components.dropend,
between=list(y=0.2),
layout=c(2,NA), as.table=TRUE)
