NRTデータを確認してみる
setwd("/Users/koyo/Dropbox/000099_oouchi/nrt_mod")
# NRTデータの読み込み
nrt.234.1_ <- read.csv("CSR_27_1.csv")
nrt.234.2_ <- read.csv("CSR_27_2.csv")
nrt.345.1_ <- read.csv("CSR_27_3.csv")
nrt.345.2_ <- read.csv("CSR_27_4.csv")
nrt.456.1_ <- read.csv("CSR_27_5.csv")
nrt.456.2_ <- read.csv("CSR_27_6.csv")
nrt.456.3_ <- read.csv("CSR_27_7.csv")
nrt.456.4_ <- read.csv("CSR_27_8.csv")
nrt.456.5_ <- read.csv("CSR_27_9.csv")
nrt.456.6_ <- read.csv("CSR_27_10.csv")
# 必要な変数を取り出す
nrt.234.1 <- nrt.234.1_[c("gakkobango", "seibetsu", "t1koku", "t2koku", "t3koku", "t1sha", "t2sha", "t3sha", "t1san", "t2san", "t3san", "t1ri", "t2ri", "t3ri", "t1gakunen", "t1gakkyu", "t2gakunen", "t2gakkyu")]
nrt.234.2 <- nrt.234.2_[c("gakkobango", "seibetsu", "t1koku", "t2koku", "t3koku", "t1sha", "t2sha", "t3sha", "t1san", "t2san", "t3san", "t1ri", "t2ri", "t3ri", "t1gakunen", "t1gakkyu", "t2gakunen", "t2gakkyu")]
nrt.345.1 <- nrt.345.1_[c("gakkobango", "seibetsu", "t1koku", "t2koku", "t3koku", "t1sha", "t2sha", "t3sha", "t1san", "t2san", "t3san", "t1ri", "t2ri", "t3ri", "t1gakunen", "t1gakkyu", "t2gakunen", "t2gakkyu")]
nrt.345.2 <- nrt.345.2_[c("gakkobango", "seibetsu", "t1koku", "t2koku", "t3koku", "t1sha", "t2sha", "t3sha", "t1san", "t2san", "t3san", "t1ri", "t2ri", "t3ri", "t1gakunen", "t1gakkyu", "t2gakunen", "t2gakkyu")]
nrt.456.1 <- nrt.456.1_[c("gakkobango", "seibetsu", "t1koku", "t2koku", "t3koku", "t1sha", "t2sha", "t3sha", "t1san", "t2san", "t3san", "t1ri", "t2ri", "t3ri", "t1gakunen", "t1gakkyu", "t2gakunen", "t2gakkyu")]
nrt.456.2 <- nrt.456.2_[c("gakkobango", "seibetsu", "t1koku", "t2koku", "t3koku", "t1sha", "t2sha", "t3sha", "t1san", "t2san", "t3san", "t1ri", "t2ri", "t3ri", "t1gakunen", "t1gakkyu", "t2gakunen", "t2gakkyu")]
nrt.456.3 <- nrt.456.3_[c("gakkobango", "seibetsu", "t1koku", "t2koku", "t3koku", "t1sha", "t2sha", "t3sha", "t1san", "t2san", "t3san", "t1ri", "t2ri", "t3ri", "t1gakunen", "t1gakkyu", "t2gakunen", "t2gakkyu")]
nrt.456.4 <- nrt.456.4_[c("gakkobango", "seibetsu", "t1koku", "t2koku", "t3koku", "t1sha", "t2sha", "t3sha", "t1san", "t2san", "t3san", "t1ri", "t2ri", "t3ri", "t1gakunen", "t1gakkyu", "t2gakunen", "t2gakkyu")]
nrt.456.5 <- nrt.456.5_[c("gakkobango", "seibetsu", "t1koku", "t2koku", "t3koku", "t1sha", "t2sha", "t3sha", "t1san", "t2san", "t3san", "t1ri", "t2ri", "t3ri", "t1gakunen", "t1gakkyu", "t2gakunen", "t2gakkyu")]
nrt.456.6 <- nrt.456.6_[c("gakkobango", "seibetsu", "t1koku", "t2koku", "t3koku", "t1sha", "t2sha", "t3sha", "t1san", "t2san", "t3san", "t1ri", "t2ri", "t3ri", "t1gakunen", "t1gakkyu", "t2gakunen", "t2gakkyu")]
# 教科別にまとめる
shak.456_ <- rbind(nrt.456.5, nrt.456.6)
# 学校数確認
shak.456.schl <- data.frame(unique(shak.456_$gakkobango))
- 以上の結果から，「その結果，社会科の教研式NRTを実施していたのは20市町村であり，小学校86校3,075名分の第4, 5, 6学年開始前後の社会科の学力偏差値を児童個別に対応づけられた状態で取得した。」という記述は正しいことを確認した。
学校調査に2年分回答した学校
# 1年ごとの学校調査のデータ
setwd("/Users/koyo/Dropbox/000099_Oouchi/data")
h25.ss <- read_excel("H25_SS_PQ.xlsx", sheet=4, col_names=TRUE)
h26.ss <- read_excel("H26_SS_PQ_moto.xlsx", sheet=4, col_names=TRUE)
h25.ss.sid <- data.frame(h25.ss$sid)
h26.ss.sid <- data.frame(h26.ss$sid)
colnames(h25.ss.sid) <- c("sid")
colnames(h26.ss.sid) <- c("sid")
# 2年分の学校調査の回答ありの学校
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
h2526.sid <- dplyr::inner_join(h25.ss.sid, h26.ss.sid, by = "sid")
- 以上の結果から，2年分の学校調査の回答ありの学校は183校であることがわかった。
学校調査に2年分回答し，NRTデータのある学校
colnames(shak.456.schl) <- c("sid")
nrt.school <- dplyr::inner_join(shak.456.schl, h2526.sid, by = "sid")
- 以上の結果から，2年分の学校調査の回答あり，NRTデータありの学校は75校であることがわかった。
複式ではない，少人数指導をしていない学校
setwd("/Users/koyo/Dropbox/000099_Oouchi/data")
h25.hensei <- read_excel("H25_sho_hensei.xlsx", sheet=1, col_names=TRUE)
## New names:
## * `` -> ...1
h25.ss <- read_excel("H25_SS_PQ.xlsx", sheet=4, col_names=TRUE)
h25.sa <- read_excel("H25_SA_PQ_noasta.xlsx", sheet=4, col_names=TRUE)
h26.hensei <- read_excel("H26_sho_hensei.xlsx", sheet=5, col_names=TRUE)
## New names:
## * `` -> ...1
h26.ss <- read_excel("H26_SS_PQ_moto.xlsx", sheet=4, col_names=TRUE)
h26.sa <- read_excel("H26_SA_PQ_moto_noasta.xlsx", sheet=4, col_names=TRUE)
# 形成的評価実施データの作成
## 学年の限定
h25.g4.sa <- subset(h25.sa, Q1==4)
h26.g5.sa <- subset(h26.sa, Q3==5)
## 教科の限定
h25.g4.shak.sa <- h25.g4.sa
h26.g5.shak.sa <- h26.g5.sa
## 年度別のフィードバック実施状況
### 1年目・計画的FBをやりきる（その1）
h25.g4.shak.sa$kfb.t1 <- ifelse(h25.g4.shak.sa$Q20S1 == 1 &
h25.g4.shak.sa$Q22S2 == 1, 1, 0)
### 1年目・非計画的FBを半分超やりきる（その2）
h25.g4.shak.sa$hfb.t1 <- ifelse(h25.g4.shak.sa$Q23S1 < 3 &
h25.g4.shak.sa$Q23S2 < 3 &
h25.g4.shak.sa$Q25S1 < 3 &
h25.g4.shak.sa$Q25S2 < 3 &
h25.g4.shak.sa$Q23S1 > 0 &
h25.g4.shak.sa$Q23S2 > 0 &
h25.g4.shak.sa$Q25S1 > 0 &
h25.g4.shak.sa$Q25S2 > 0, 1, 0)
### 1年目・その1，2を満たす
h25.g4.shak.sa$khfb.t1 <- ifelse(h25.g4.shak.sa$kfb.t1 == 1 &
h25.g4.shak.sa$hfb.t1 == 1, 1, 0)
### 1年目・経験年数
#### 教諭・10年以下
h25.g4.shak.sa$kei10 <- ifelse(h25.g4.shak.sa$Q37 == 2 & h25.g4.shak.sa$Q38 <11, 1, 0)
#### 教諭・20年以下
h25.g4.shak.sa$kei20 <- ifelse(h25.g4.shak.sa$Q37 == 2 & h25.g4.shak.sa$Q38 < 21 & h25.g4.shak.sa$Q38 >10, 1, 0)
#### 教諭・21年以上
h25.g4.shak.sa$kei21 <- ifelse(h25.g4.shak.sa$Q37 == 2 & h25.g4.shak.sa$Q38 >20, 1, 0)
#### 10年以下かどうか
h25.g4.shak.sa$kei3c1 <- ifelse(h25.g4.shak.sa$Q37 == 1 | h25.g4.shak.sa$kei10 ==1, 1, 0)
h25.g4.shak.sa$kei3c2 <- ifelse(h25.g4.shak.sa$kei20 ==1, 1, 0)
h25.g4.shak.sa$kei3c3 <- ifelse(h25.g4.shak.sa$Q37 == 3 | h25.g4.shak.sa$kei21 ==1, 1, 0)
#### 20年以下かどうか
h25.g4.shak.sa$kei2c1 <- ifelse(h25.g4.shak.sa$Q37 == 1 | h25.g4.shak.sa$kei10 ==1, 1, 0)
h25.g4.shak.sa$kei2c2 <- ifelse(h25.g4.shak.sa$kei3c1 == 1 | h25.g4.shak.sa$kei3c2 ==1, 1, 0)
### 2年目・計画的FBをやりきる（その1）
h26.g5.shak.sa$kfb.t2 <- ifelse(h26.g5.shak.sa$Q22S1 == 1 &
h26.g5.shak.sa$Q24S2 == 1, 1, 0)
### 2年目・非計画的FBを半分超やりきる（その2）
h26.g5.shak.sa$hfb.t2 <- ifelse(h26.g5.shak.sa$Q25S1 < 3 &
h26.g5.shak.sa$Q25S2 < 3 &
h26.g5.shak.sa$Q27S1 < 3 &
h26.g5.shak.sa$Q27S2 < 3 &
h26.g5.shak.sa$Q25S1 > 0 &
h26.g5.shak.sa$Q25S2 > 0 &
h26.g5.shak.sa$Q27S1 > 0 &
h26.g5.shak.sa$Q27S2 > 0 , 1, 0)
### 2年目・その1，2を満たす
h26.g5.shak.sa$khfb.t2 <- ifelse(h26.g5.shak.sa$kfb.t2 == 1 &
h26.g5.shak.sa$hfb.t2 == 1, 1, 0)
### 2年目・経験年数
#### 教諭・10年以下
h26.g5.shak.sa$kei10 <- ifelse(h26.g5.shak.sa$Q44 == 2 & h26.g5.shak.sa$Q45 <11, 1, 0)
#### 教諭・20年以下
h26.g5.shak.sa$kei20 <- ifelse(h26.g5.shak.sa$Q44 == 2 & h26.g5.shak.sa$Q45 < 21 & h26.g5.shak.sa$Q45 >10, 1, 0)
#### 教諭・21年以上
h26.g5.shak.sa$kei21 <- ifelse(h26.g5.shak.sa$Q44 == 2 & h26.g5.shak.sa$Q45 >20, 1, 0)
#### 10年以下かどうか
h26.g5.shak.sa$kei3c1 <- ifelse(h26.g5.shak.sa$Q44 == 1 | h26.g5.shak.sa$kei10 ==1, 1, 0)
h26.g5.shak.sa$kei3c2 <- ifelse(h26.g5.shak.sa$kei20 ==1, 1, 0)
h26.g5.shak.sa$kei3c3 <- ifelse(h26.g5.shak.sa$Q44 == 3 | h26.g5.shak.sa$kei21 ==1, 1, 0)
#### 20年以下かどうか
h26.g5.shak.sa$kei2c1 <- ifelse(h26.g5.shak.sa$Q44 == 1 | h26.g5.shak.sa$kei10 ==1, 1, 0)
h26.g5.shak.sa$kei2c2 <- ifelse(h26.g5.shak.sa$kei3c1 == 1 | h26.g5.shak.sa$kei3c2 ==1, 1, 0)
# 学校別学年別平均学級規模データの作成
## 1時点目（第4学年）
h25.g4.hensei.all <- subset(h25.hensei, g==4)
## 2時点目（第5学年）
h26.g5.hensei.all <- subset(h26.hensei, g==5)
## 0人学級の列を削除
h25.g4.hensei <- subset(h25.g4.hensei.all, pupil>0)
h26.g5.hensei <- subset(h26.g5.hensei.all, pupil>0)
## 学校別年度別平均学級規模を求める
h25.g4.csmean.tab <- tapply(h25.g4.hensei$pupil, h25.g4.hensei$sid, mean)
h26.g5.csmean.tab <- tapply(h26.g5.hensei$pupil, h26.g5.hensei$sid, mean)
### 集計結果を行ったり来たりさせてデータ化する
setwd("/Users/koyo/Dropbox/000099_oouchi/160618/df2csv2df")
h25.g4.csmean.df <- data.frame(h25.g4.csmean.tab)
write.csv(h25.g4.csmean.df, "h25_g4_csmean.csv")
h25.g4.csmean <- read.csv("h25_g4_csmean.csv")
colnames(h25.g4.csmean) <- c("sid", "cs.t1.m")
h26.g5.csmean.df <- data.frame(h26.g5.csmean.tab)
write.csv(h26.g5.csmean.df, "h26_g5_csmean.csv")
h26.g5.csmean <- read.csv("h26_g5_csmean.csv")
colnames(h26.g5.csmean) <- c("sid", "cs.t2.m")
setwd("/Users/koyo/Dropbox/000099_oouchi/160618")
## 2時点をまとめる
csmean.456 <- merge(h25.g4.csmean, h26.g5.csmean, by="sid", all=T)
# 学校別学年別学級数データの作成
## 1時点目
h25.g4.nc.all <- h25.g4.hensei[c("sid", "nc_by_g")]
h25.g4.nc <- unique(h25.g4.nc.all )
colnames(h25.g4.nc) <- c("sid", "nc.t1")
## 2時点目
h26.g5.nc.all <- h26.g5.hensei[c("sid", "nc_by_g")]
h26.g5.nc <- unique(h26.g5.nc.all )
colnames(h26.g5.nc) <- c("sid", "nc.t2")
## 2時点をまとめる
nc.456 <- merge(h25.g4.nc, h26.g5.nc, by="sid", all=T)
# 学校別学年別平均学級規模・学級数データの作成
## csmeanとncをマージ
cs.nc.456.mae <- merge(csmean.456, nc.456, by="sid", all=T)
## 2年間の学級数が同じという変数を加える
cs.nc.456.mae$ncsame <- ifelse(cs.nc.456.mae$nc.t1 == cs.nc.456.mae$nc.t2, 1, 0)
## ncistanを加える
cs.nc.456.mae$ncistan <- ifelse(cs.nc.456.mae$nc.t1 == 1 & cs.nc.456.mae$nc.t2 == 1, 1, 0)
## 2年間の平均学級規模を加える
cs.nc.456 <- transform(cs.nc.456.mae, csmean =((cs.t1.m + cs.t2.m)/2))
## 2年間学級数が同じ学校に学級数の変数を追加する
cs.nc.456$nc <- ifelse(cs.nc.456$ncsame == 1, cs.nc.456$nc.t1, 0)
# 少人数指導等実施有無データの作成
## TTを含む少人数指導なしの学校
h25.g4.shak.nott_ <- subset(h25.ss, Q9S2_4==1)
h26.g5.shak.nott_ <- subset(h26.ss, Q11S2_4==1)
h25.g4.shak.nott.s <- h25.g4.shak.nott_[c("sid")]
h26.g5.shak.nott.s <- h26.g5.shak.nott_[c("sid")]
shak.456.nott <- merge(h25.g4.shak.nott.s, h26.g5.shak.nott.s)
# 分析対象校・学級規模等・学力データの結合
## TT含む少人数指導なしの学校
shak.456.sc.nscs.all <- merge(shak.456.nott, cs.nc.456)
- 複式ではない，少人数指導をしていない学校は138校
複式ではない，少人数指導をしていない，456年の社会科NRTデータのある学校
colnames(shak.456.schl) <- c("sid")
library(dplyr)
taishoko <- dplyr::inner_join(shak.456.sc.nscs.all, shak.456.schl, by = "sid")
- 複式ではない，少人数指導をしていない，456年の社会科NRTデータのある学校は53校
2年分の教師データがとれた児童数と学級数の確認
### 教科別に加工する
shak.456 <- shak.456_[c("gakkobango", "seibetsu", "t1sha", "t2sha", "t3sha", "t1gakunen", "t1gakkyu", "t2gakunen", "t2gakkyu")]
shak.456 <- transform(shak.456, sgcid.t1=(paste(gakkobango, t1gakunen, t1gakkyu ,sep="")))
shak.456 <- transform(shak.456, sgcid.t2=(paste(gakkobango, t2gakunen, t2gakkyu ,sep="")))
## センタリングの変数を作る
### 計算しやすくするために変数名を変え，NAなしにする
nrt.cn <- c("sid", "sex", "t1", "t2", "t3", "g.t1", "c.t1", "g.t2", "c.t2", "sgcid.t1", "sgcid.t2")
colnames(shak.456) <- nrt.cn
shak.456 <- na.omit(shak.456)
### T1の学力偏差値を50で引く
shak.456 <- transform(shak.456, t1m50=(t1-50))
### T2の学力偏差値を50で引く
shak.456 <- transform(shak.456, t2m50=(t2-50))
### T3の学力偏差値を50で引く
shak.456 <- transform(shak.456, t3m50=(t3-50))
### t1m50の学校平均を出す
shak.456.t1m50sm.df <- data.frame(tapply(shak.456$t1m50, shak.456$sid, mean))
setwd("/Users/koyo/Dropbox/000099_oouchi/200705/df2csv2df")
write.csv(shak.456.t1m50sm.df, "shak_456_t1m50sm.csv")
shak.456.t1m50sm <- read.csv("shak_456_t1m50sm.csv")
colnames(shak.456.t1m50sm) <- c("sid", "t1m50sm")
setwd("/Users/koyo/Dropbox/000099_oouchi/200705")
### t2m50の学校平均を出す
shak.456.t2m50sm.df <- data.frame(tapply(shak.456$t2m50, shak.456$sid, mean))
setwd("/Users/koyo/Dropbox/000099_oouchi/200705/df2csv2df")
write.csv(shak.456.t2m50sm.df, "shak_456_t2m50sm.csv")
shak.456.t2m50sm <- read.csv("shak_456_t2m50sm.csv")
colnames(shak.456.t2m50sm) <- c("sid", "t2m50sm")
setwd("/Users/koyo/Dropbox/000099_oouchi/200705")
### t1m50smとt2m50smをマージする
shak.456.w.dm <- merge(shak.456.t1m50sm, shak.456.t2m50sm, by="sid")
### t1m50smとt2m50smをマージしたものを学力検査データにマージする
shak.456.w.sm <- merge(shak.456, shak.456.w.dm, by="sid")
### 児童偏差得点（t1m50-t1m50sm）の追加
shak.456.w.hens1 <- transform(shak.456.w.sm, jido.hensa.t1 = (t1m50 - t1m50sm))
### 児童偏差得点（t2m50-t2m50sm）の追加
shak.456.w.hensa <- transform(shak.456.w.hens1, jido.hensa.t2 = (t2m50 - t2m50sm))
# 分析対象校・学級規模等・学力データの結合
## TT含む少人数指導なしの学校
shak.456.sc.nscs.all <- merge(shak.456.nott, cs.nc.456)
### 学級数変動のあった学校を除外することは止めておく
#shak.456.sc.nscs <- subset(shak.456.sc.nscs.all, ncsame ==1)
shak.456.sc.nscs <- shak.456.sc.nscs.all
## 学力データの結合
shak.456.sc.nscs.nrt <- merge(shak.456.w.hensa, shak.456.sc.nscs, by="sid")
# フィードバック実施状況の結合
## フィードバックデータの整形
h25.g4.shak.fb <- h25.g4.shak.sa[c("scgid","kfb.t1", "hfb.t1", "khfb.t1", "kei3c1", "kei3c2", "kei3c3", "kei2c1", "kei2c2")]
colnames(h25.g4.shak.fb) <- c("sgcid.t1", "kfb.t1", "hfb.t1", "khfb.t1", "kei3c1.t1", "kei3c2.t1", "kei3c3.t1", "kei2c1.t1", "kei2c2.t1")
h26.g5.shak.fb <- h26.g5.shak.sa[c("scgid","kfb.t2", "hfb.t2", "khfb.t2", "kei3c1", "kei3c2", "kei3c3", "kei2c1", "kei2c2")]
colnames(h26.g5.shak.fb) <- c("sgcid.t2", "kfb.t2", "hfb.t2", "khfb.t2", "kei3c1.t2", "kei3c2.t2", "kei3c3.t2", "kei2c1.t2", "kei2c2.t2")
### 結合
shak.456.fb.t1 <- merge(shak.456.sc.nscs.nrt, h25.g4.shak.fb, by="sgcid.t1")
shak.456.fb <- merge(shak.456.fb.t1, h26.g5.shak.fb, by="sgcid.t2")
## 2年度間通しの状況
shak.456.fb$kfb <- ifelse(shak.456.fb$kfb.t1 ==1 & shak.456.fb$kfb.t2 ==1, 1, 0)
shak.456.fb$hfb <- ifelse(shak.456.fb$hfb.t1 ==1 & shak.456.fb$hfb.t2 ==1, 1, 0)
shak.456.fb$khfb <- ifelse(shak.456.fb$khfb.t1 ==1 & shak.456.fb$khfb.t2 ==1, 1, 0)
# 3レベル用の変数作成
## 2年間通しの学校学年学級IDを振る
shak.456.fb <- transform(shak.456.fb, SG4G5ID = (paste(sid, g.t1, c.t1, g.t2, c.t2, sep="")))
## t1m50の2年間通し学級平均を出す
shak.456.fb.t1m50cm.df <- data.frame(tapply(shak.456.fb$t1m50, shak.456.fb$SG4G5ID, mean))
## t2m50の2年間通し学級平均を出す
shak.456.fb.t2m50cm.df <- data.frame(tapply(shak.456.fb$t2m50, shak.456.fb$SG4G5ID, mean))
### データの加工
setwd("/Users/koyo/Dropbox/000099_oouchi/200705/df2csv2df")
write.csv(shak.456.fb.t1m50cm.df, "shak_456_t1m50cm.csv")
shak.456.fb.t1m50cm <- read.csv("shak_456_t1m50cm.csv")
colnames(shak.456.fb.t1m50cm) <- c("SG4G5ID", "t1m50cm")
write.csv(shak.456.fb.t2m50cm.df, "shak_456_t2m50cm.csv")
shak.456.fb.t2m50cm <- read.csv("shak_456_t2m50cm.csv")
colnames(shak.456.fb.t2m50cm) <- c("SG4G5ID", "t2m50cm")
setwd("/Users/koyo/Dropbox/000099_oouchi/200705")
## t1m50cmの学校平均を出す(PreL3)
shak.456.fb.t1m50cm <- transform(shak.456.fb.t1m50cm, sid = (substr(SG4G5ID, 1, 4)))
shak.456.fb.t1m50cm.sm.df <- data.frame(tapply(shak.456.fb.t1m50cm$t1m50cm, shak.456.fb.t1m50cm$sid, mean))
shak.456.fb.t2m50cm <- transform(shak.456.fb.t2m50cm, sid = (substr(SG4G5ID, 1, 4)))
shak.456.fb.t2m50cm.sm.df <- data.frame(tapply(shak.456.fb.t2m50cm$t2m50cm, shak.456.fb.t2m50cm$sid, mean))
### データの加工
setwd("/Users/koyo/Dropbox/000099_oouchi/200705/df2csv2df")
write.csv(shak.456.fb.t1m50cm.sm.df, "shak_456_t1m50cmsm.csv")
shak.456.fb.t1m50cm.sm <- read.csv("shak_456_t1m50cmsm.csv")
colnames(shak.456.fb.t1m50cm.sm) <- c("sid", "t1m50cmsm")
write.csv(shak.456.fb.t2m50cm.sm.df, "shak_456_t2m50cmsm.csv")
shak.456.fb.t2m50cm.sm <- read.csv("shak_456_t2m50cmsm.csv")
colnames(shak.456.fb.t2m50cm.sm) <- c("sid", "t2m50cmsm")
setwd("/Users/koyo/Dropbox/000099_oouchi/200705")
## 学級偏差平均（t1m50cm - t1m50cmsm）を求める(PreL2)
shak.456.fb.t1m50cm.m.cmsm <- merge(shak.456.fb.t1m50cm, shak.456.fb.t1m50cm.sm, by="sid", all=T)
shak.456.fb.t1m50cm.m.cmsm <- transform(shak.456.fb.t1m50cm.m.cmsm, t1m50cm.m.cmsm =(t1m50cm - t1m50cmsm))
## 学級偏差平均（t2m50cm - t2m50cmsm）を求める(PreL2t2)
shak.456.fb.t2m50cm.m.cmsm <- merge(shak.456.fb.t2m50cm, shak.456.fb.t2m50cm.sm, by="sid", all=T)
shak.456.fb.t2m50cm.m.cmsm <- transform(shak.456.fb.t2m50cm.m.cmsm, t2m50cm.m.cmsm =(t2m50cm - t2m50cmsm))
## 後のことを考えて名前を変えておく
colnames(shak.456.fb.t1m50cm.m.cmsm) <- c("sid", "SG4G5ID", "t1m50cm", "PreL3", "PreL2")
colnames(shak.456.fb.t2m50cm.m.cmsm) <- c("sid", "SG4G5ID", "t2m50cm", "PreL3t2", "PreL2t2")
### マージに使わない変数を消しておく
shak.456.fb.t1m50cm.m.cmsm <- shak.456.fb.t1m50cm.m.cmsm[c("SG4G5ID", "t1m50cm", "PreL3", "PreL2")]
shak.456.fb.t2m50cm.m.cmsm <- shak.456.fb.t2m50cm.m.cmsm[c("SG4G5ID", "t2m50cm", "PreL3t2", "PreL2t2")]
## 児童偏差得点を求める(t1m50 - t1m50cm)（PreL1)
shak.456.dummy <- merge(shak.456.fb.t1m50cm.m.cmsm, shak.456.fb.t2m50cm.m.cmsm, by="SG4G5ID")
shak.456 <- merge(shak.456.fb, shak.456.dummy, by="SG4G5ID")
shak.456 <- transform(shak.456, PreL1 = (t1m50 - t1m50cm))
shak.456 <- transform(shak.456, PreL1t2 = (t2m50 - t2m50cm))
## 学級規模と交互作用の変数をつくる
shak.456 <- transform(shak.456, CS45M24 = (csmean - 24))
shak.456 <- transform(shak.456, INTERACT = (CS45M24 * kfb))
shak.456 <- transform(shak.456, NCM1 = (nc-1))
# 学級別学級規模を拾う
each.cs.t1 <- h25.g4.hensei[c("sgcid", "pupil")]
each.cs.t2 <- h26.g5.hensei[c("sgcid", "pupil")]
## 変数名変更
colnames(each.cs.t1) <- c("sgcid.t1", "ecst1")
colnames(each.cs.t2) <- c("sgcid.t2", "ecst2")
## マージする
shak.456.ecs1 <- merge(shak.456, each.cs.t1, by="sgcid.t1")
shak.456.ecs <- merge(shak.456.ecs1, each.cs.t2, by="sgcid.t2")
## 24で引く
shak.456.ecs <- transform(shak.456.ecs, ecst1m24 = ecst1-24)
shak.456.ecs <- transform(shak.456.ecs, ecst2m24 = ecst2-24)
shak.456.ecs <- transform(shak.456.ecs, cs.t1.m.m24 = cs.t1.m-24)
shak.456.ecs <- transform(shak.456.ecs, cs.t2.m.m24 = cs.t2.m-24)
##時点別の学級規模とフィードバックの交互作用をつくる
shak.456.ecs <- transform(shak.456.ecs, INTER.t1 = (ecst1m24 * kfb.t1))
shak.456.ecs <- transform(shak.456.ecs, INTER.t2 = (ecst2m24 * kfb.t2))
nrow(data.frame(unique(shak.456.ecs$sid)))
## [1] 52
- 複式ではない，少人数指導をしていない，456年の社会科NRTデータがある，2年分の教師データがとれた学校は52校
クラスサイズ変動の状況を確認する
cs.t1.m <- data.frame(unique(shak.456.ecs[c("sid", "cs.t1.m")]))
cs.t2.m <- data.frame(unique(shak.456.ecs[c("sid", "cs.t2.m")]))
cs.t12.m <- dplyr::inner_join(cs.t1.m, cs.t2.m, by = "sid")
cs.t12.m <- dplyr::mutate(cs.t12.m, diff = cs.t1.m - cs.t2.m)
table(cs.t12.m$diff)
##
## -1.5 -1 -0.6666666666667 -0.5
## 1 5 1 3
## -0.3333333333334 0 0.3333333333333 0.5
## 1 31 1 2
## 1 2 10.3333333333333
## 5 1 1
nrow(shak.456.ecs)
## [1] 1791