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#contents

*データ
-Table 3.6.1 (p.64)

|Sequence|SID|Period1|Period2|
|RT|1|74.675|73.675|
|RT|4|96.4|93.25|
|RT|5|101.95|102.125|
|RT|6|79.05|69.45|
|RT|11|79.05|69.025|
|RT|12|85.95|68.7|
|RT|15|69.725|59.425|
|RT|16|86.275|76.125|
|RT|19|112.675|114.875|
|RT|20|99.525|116.25|
|RT|23|89.425|64.175|
|RT|24|55.175|74.575|
|TR|2|74.825|37.35|
|TR|3|86.875|51.925|
|TR|7|81.675|72.175|
|TR|8|92.7|77.5|
|TR|9|50.45|71.875|
|TR|10|66.125|94.025|
|TR|13|122.45|124.975|
|TR|14|99.075|85.225|
|TR|17|86.35|95.925|
|TR|18|49.925|67.1|
|TR|21|42.7|59.425|
|TR|22|91.725|114.05|

*プログラムと結果

>library(nlme)
>tab361 <- read.table("table361.csv", sep=",", header=T)

>nrow1 <- nrow(tab361)
>sequence <- rep(tab361$Sequence, rep(2, nrow1))
>SID <- rep(tab361$SID, rep(2, nrow1))
>Period <- rep(1:2, nrow1)
>Drug <- rep(" ", nrow1*2)
>y <- double(nrow1*2)
 
>for (i in seq(nrow1)) {
>if (tab361$Sequence[i] == "RT") {
>Drug[i*2-1] = "R"
>Drug[i*2] = "T"
>} else {
>Drug[i*2-1] = "T"
>Drug[i*2] = "R"
>}
>y[i*2-1] = tab361$Period1[i]
>y[i*2] = tab361$Period2[i]
>}

>tab361.2 <- data.frame(Sequence=sequence, SID, Period=as.factor(Period), Drug, y)

>fm1.lme <- lme(y ~ Sequence+Period+Drug, data=tab361.2, random=~1 | SID)
>anova(fm1.lme)

             numDF denDF  F-value p-value
 (Intercept)     1    22 431.7741  <.0001
 Sequence        1    22   0.3745  0.5468
 Period          1    22   0.2151  0.6474
 Drug            1    22   0.3754  0.5463

*参照
-[[Chow&Liu]]
-[[R]]

#contents

*データ
-Table 3.6.1 (p.64)

|Sequence|SID|Period1|Period2|
|RT|1|74.675|73.675|
|RT|4|96.4|93.25|
|RT|5|101.95|102.125|
|RT|6|79.05|69.45|
|RT|11|79.05|69.025|
|RT|12|85.95|68.7|
|RT|15|69.725|59.425|
|RT|16|86.275|76.125|
|RT|19|112.675|114.875|
|RT|20|99.525|116.25|
|RT|23|89.425|64.175|
|RT|24|55.175|74.575|
|TR|2|74.825|37.35|
|TR|3|86.875|51.925|
|TR|7|81.675|72.175|
|TR|8|92.7|77.5|
|TR|9|50.45|71.875|
|TR|10|66.125|94.025|
|TR|13|122.45|124.975|
|TR|14|99.075|85.225|
|TR|17|86.35|95.925|
|TR|18|49.925|67.1|
|TR|21|42.7|59.425|
|TR|22|91.725|114.05|

*プログラムと結果
**変量効果モデル

>library(nlme)
>tab361 <- read.table("table361.csv", sep=",", header=T)

>nrow1 <- nrow(tab361)
>sequence <- rep(tab361$Sequence, rep(2, nrow1))
>SID <- rep(tab361$SID, rep(2, nrow1))
>Period <- rep(1:2, nrow1)
>Drug <- rep(" ", nrow1*2)
>y <- double(nrow1*2)
 
>for (i in seq(nrow1)) {
>if (tab361$Sequence[i] == "RT") {
>Drug[i*2-1] = "R"
>Drug[i*2] = "T"
>} else {
>Drug[i*2-1] = "T"
>Drug[i*2] = "R"
>}
>y[i*2-1] = tab361$Period1[i]
>y[i*2] = tab361$Period2[i]
>}

>tab361.2 <- data.frame(Sequence=sequence, SID, Period=as.factor(Period), Drug, y)

>fm1.lme <- lme(y ~ Sequence+Period+Drug, data=tab361.2, random=~1 | SID)
>anova(fm1.lme)

             numDF denDF  F-value p-value
 (Intercept)     1    22 431.7741  <.0001
 Sequence        1    22   0.3745  0.5468
 Period          1    22   0.2151  0.6474
 Drug            1    22   0.3754  0.5463

**Split-plot モデル

>fm2.aov <- aov(y ~ Sequence+Period+Drug+Error(factor(SID)), tab361.2)
>summary(fm2.aov)

 Error: factor(SID)
           Df  Sum Sq Mean Sq F value Pr(>F)
 Sequence   1   276.0   276.0  0.3745 0.5468
 Residuals 22 16211.5   736.9               

 Error: Within
           Df Sum Sq Mean Sq F value Pr(>F)
 Period     1   36.0    36.0  0.2151 0.6474
 Drug       1   62.8    62.8  0.3754 0.5463
 Residuals 22 3679.4   167.2

*参照
-[[Chow&Liu]]
-[[R]]