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Output summary tables
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#Read in edited data including SDs and BMIs
setwd("c:/Users/mqbpjhr4/Documents/CHAMP")
alldata<-read.table ("LMStableedited.csv",header=TRUE, sep=",")
names(alldata)[names(alldata)=="X"] <- "SDS_BMI"
#LOCAL:
alldata$weightcat<-"normal"
alldata$weightcat[alldata$Centile_BMI>=90.879]<-"overweight"
alldata$weightcat[alldata$Centile_BMI>=97.725]<-"obese"
alldata$weightcat[alldata$Centile_BMI>=99.617]<-"severely_obese"
alldata$weightcat[alldata$Centile_BMI>=99.913]<-"morbidly_obese"
alldata$weightcat[alldata$Centile_BMI<=2.275]<-"underweight"
alldata$weightcat[alldata$Centile_BMI<=0.383]<-"very_underweight"
#Assessing CHAMP uptake
table(alldata$weightcat,alldata$IsAccountRegistered)
#Champ reg 2013/14 25.74
#Champ reg 2014/15 33.78
#Champ reg 2015/16 26.51
#Champ reg 2016/17 25.89
table(alldata$weightcat,alldata$IsAccountRegistered)
#ex ob 31.20
#morb ob 30.94
#ob 32.58
#normal 39.66
#ov 37.52
#un 36.67
#v. un 29.81
#sev un 31.68
#CREATE DATA SUBSET FOR THIS YEAR'S DATA
thisyear<-subset(alldata, alldata$AcademicYear=="2014/2015" & alldata$BMI<50)
library(lubridate)
#CALCULATE CLASS WHEN MEASURED (Install Lubridate)
ndate1<-paste(DateOfBirth,"-01",sep=""); ndate1
ndate2<-paste(AssessmentDate,"-01",sep=""); ndate1
thisyear$DateOfBirth<-(as.Date(ndate1))
thisyear$AssessmentDate<-(as.Date(ndate2))
thisyear$sumage<-round(thisyear$ageattestyr,digits=0)
thisyear$birthmonth<-month(as.POSIXlt(thisyear$DateOfBirth, format="%Y-%m-%d"))
thisyear$assmonth<-month(as.POSIXlt(thisyear$AssessmentDate, format="%Y-%m"))
thisyear$class<-NA
thisyear$ageattestyr<-floor(thisyear$ageattest/52.149) #Round year down to give age
thisyear$class<-ifelse(thisyear$ageattestyr==4,0,thisyear$class) #All 4 year olds are in Reception
thisyear$class<-ifelse(thisyear$ageattestyr==5,1,thisyear$class) #most 5 year olds are in year one
thisyear$class<-ifelse(thisyear$birthmonth>=9 & thisyear$ageattestyr==5 &thisyear$assmonth>8,0,thisyear$class) #5 year olds that have a birthday from September onwards that are measured in the autumn term are in Reception
thisyear$class<-ifelse(thisyear$birthmonth<=thisyear$assmonth & thisyear$ageattestyr==5 &thisyear$assmonth<=8,0,thisyear$class) #5 year olds with a birthday before September that are measured in the spring term are in Reception
thisyear$class<-ifelse(thisyear$ageattestyr==6,2,thisyear$class) # most 6 year olds are in year 2
thisyear$class<-ifelse(thisyear$birthmonth>=9 & thisyear$ageattestyr==6&thisyear$assmonth>8,1,thisyear$class) #6 year olds that have a birthday from September onwards that are measured in the autumn term are in Reception
thisyear$class<-ifelse(thisyear$birthmonth<=thisyear$assmonth & thisyear$ageattestyr==6 &thisyear$assmonth<=8,1,thisyear$class) #6 year olds with a birthday before September that are measured in the spring term are in Reception
thisyear$class<-ifelse(thisyear$ageattestyr==7,3,thisyear$class) # most 7 year olds are in year 3
thisyear$class<-ifelse(thisyear$birthmonth>=9 & thisyear$ageattestyr==7 &thisyear$assmonth>8,2,thisyear$class) #7 year olds that have a birthday from September onwards that are measured in the autumn term are in yr1
thisyear$class<-ifelse(thisyear$birthmonth<=thisyear$assmonth & thisyear$ageattestyr==7 &thisyear$assmonth<=8,2,thisyear$class) #7 year olds with a birthday before September that are measured in the spring term are in yr1
thisyear$class<-ifelse(thisyear$ageattestyr==8,4,thisyear$class) # most 8 year olds are in year 4
thisyear$class<-ifelse(thisyear$birthmonth>=9 & thisyear$ageattestyr==8 &thisyear$assmonth>8,3,thisyear$class) #8 year olds that have a birthday from September onwards that are measured in the autumn term are in yr3
thisyear$class<-ifelse(thisyear$birthmonth<=thisyear$assmonth & thisyear$ageattestyr==8 &thisyear$assmonth<=8,3,thisyear$class) #8 year olds with a birthday before September that are measured in the spring term are in yr3
thisyear$class<-ifelse(thisyear$ageattestyr==9,5,thisyear$class) # most 9 year olds are in year 5
thisyear$class<-ifelse(thisyear$birthmonth>=9 & thisyear$ageattestyr==9 &thisyear$assmonth>8,4,thisyear$class) #9 year olds that have a birthday from September onwards that are measured in the autumn term are in yr4
thisyear$class<-ifelse(thisyear$birthmonth<=thisyear$assmonth & thisyear$ageattestyr==9 &thisyear$assmonth<=8,4,thisyear$class) #9 year olds with a birthday before September that are measured in the spring term are in yr4
thisyear$class<-ifelse(thisyear$ageattestyr==10,6,thisyear$class) # most 10 year olds are in year 6
thisyear$class<-ifelse(thisyear$birthmonth>=9 & thisyear$ageattestyr==10 &thisyear$assmonth>8,5,thisyear$class) #10 year olds that have a birthday from September onwards that are measured in the autumn term are in yr5
thisyear$class<-ifelse(thisyear$birthmonth<=thisyear$assmonth & thisyear$ageattestyr==10 &thisyear$assmonth<=8,5,thisyear$class) #10 year olds with a birthday before September that are measured in the spring term are in yr5
thisyear$class<-ifelse(thisyear$ageattestyr==11,6,thisyear$class)
champ2<-thisyear
thisyear$SchoolYear<-thisyear$class
attach(thisyear)
thisyear$Overweight<-as.numeric(ifelse(thisyear$Centile_BMI>=90.879,c("1"),("0")))
thisyear$Overweight<-as.numeric(thisyear$Overweight)
thisyear$Obese<-as.numeric(ifelse(Centile_BMI>=97.725,c("1"),("0")))
thisyear$Obese<-as.numeric(thisyear$Obese)
thisyear$sObese<-as.numeric(ifelse(thisyear$Centile_BMI>=99.617,c("1"),("0")))
thisyear$sObese<-as.numeric(thisyear$sObese)
thisyear$mObese<-as.numeric(ifelse(thisyear$Centile_BMI>=99.913,c("1"),("0")))
thisyear$mObese<-as.numeric(thisyear$mObese)
thisyear$Underweight<-as.numeric(ifelse(thisyear$Centile_BMI<=2.275,c("1"),("0")))
thisyear$Underweight<-as.numeric(thisyear$Underweight)
thisyear$vUnderweight<-as.numeric(ifelse(thisyear$Centile_BMI<=0.383,c("1"),("0")))
thisyear$vUnderweight<-as.numeric(thisyear$vUnderweight)
#AGGREGATE VALUES BY AGE AND GENDER
thisyear$SchoolYear<-thisyear$class
attach(thisyear)
aggdatamean <-aggregate(thisyear, by=list(Gender,SchoolYear), FUN=mean, na.rm=TRUE)
names(aggdatamean)[names(aggdatamean)=="BMI"] <- "MeanBMI"
aggSD <-aggregate(BMI, by=list(Gender,SchoolYear), sd, na.rm=TRUE)
names(aggSD)[names(aggSD)=="x"] <- "BMISD"
aggdatamedian <-aggregate(BMI, by=list(Gender,SchoolYear), median, na.rm=TRUE)
names(aggdatamedian)[names(aggdatamedian)=="x"]<- "MedianBMI"
aggdataobsums <-aggregate(thisyear$Obese, by=list(Gender,SchoolYear), FUN=sum, na.rm=TRUE)
names(aggdataobsums)[names(aggdataobsums)=="x"] <- "TotalObese"
aggdatasobsums <-aggregate(thisyear$sObese, by=list(Gender,SchoolYear), FUN=sum, na.rm=TRUE)
names(aggdatasobsums)[names(aggdatasobsums)=="x"] <- "TotalSeverelyObese"
aggdataovsums <-aggregate(thisyear$Overweight, by=list(Gender,SchoolYear), FUN=sum, na.rm=TRUE)
names(aggdataovsums)[names(aggdataovsums)=="x"] <- "TotalOverweight"
aggdataunsums <-aggregate(thisyear$Underweight, by=list(Gender,SchoolYear), FUN=sum, na.rm=TRUE)
names(aggdataunsums)[names(aggdataunsums)=="x"] <- "TotalUnderweight"
aggdatavunsums <-aggregate(thisyear$vUnderweight, by=list(Gender,SchoolYear), FUN=sum, na.rm=TRUE)
names(aggdatavunsums)[names(aggdatavunsums)=="x"] <- "TotalVeryUnderweight"
aggdatamosums <-aggregate(thisyear$mObese, by=list(Gender,SchoolYear), FUN=sum, na.rm=TRUE)
names(aggdatamosums)[names(aggdatamosums)=="x"] <- "TotalMorbidlyObese"
thisyear$ChildID<-"1"
thisyear$ChildID<-as.numeric(thisyear$ChildID)
aggdatasums <-aggregate(thisyear$ChildID, by=list(Gender,SchoolYear), FUN=sum, na.rm=TRUE)
names(aggdatasums)[names(aggdatasums)=="x"] <- "TotalChildren"
summarydata0<-merge(aggdatamean,aggdatamedian,all=TRUE, by=c('Group.1','Group.2'))
summarydata1<-merge(summarydata0,aggdataunsums,all=TRUE, by=c('Group.1','Group.2'))
summarydata2<-merge(summarydata1,aggdataovsums,all=TRUE, by=c('Group.1','Group.2'))
summarydata3<-merge(summarydata2,aggdataobsums,all=TRUE, by=c('Group.1','Group.2'))
summarydata4<-merge(summarydata3,aggdatamosums,all=TRUE, by=c('Group.1','Group.2'))
summarydata5<-merge(summarydata4,aggdatasums,all=TRUE, by=c('Group.1','Group.2'))
summarydata5b<-merge(summarydata5,aggdatavunsums,all=TRUE, by=c('Group.1','Group.2'))
summarydata5c<-merge(summarydata5b,aggdatasobsums,all=TRUE, by=c('Group.1','Group.2'))
summarydata6<-merge(summarydata5c,aggSD,all=TRUE, by=c('Group.1','Group.2'))
library(plyr)
Props<-ddply(summarydata6,.(Group.1,Group.2),transform,prop=TotalUnderweight/sum(summarydata6$TotalChildren))
names(Props)[names(Props)=="prop"] <- "PropUnderweight"
Props2<-ddply(Props,.(Group.1,Group.2),transform,prop=TotalOverweight/sum(TotalChildren))
names(Props2)[names(Props2)=="prop"] <- "PropOverweight"
Props3<-ddply(Props2,.(Group.1,Group.2),transform,prop=TotalObese/sum(TotalChildren))
names(Props3)[names(Props3)=="prop"] <- "PropObese"
Props4a<-ddply(Props3,.(Group.1,Group.2),transform,prop=TotalMorbidlyObese/sum(TotalChildren))
names(Props4a)[names(Props4a)=="prop"] <- "PropMorbidlyObese"
Props4b<-ddply(Props4a,.(Group.1,Group.2),transform,prop=TotalSeverelyObese/sum(TotalChildren))
names(Props4b)[names(Props4b)=="prop"] <- "PropSeverelyObese"
Props4<-ddply(Props4b,.(Group.1,Group.2),transform,prop=TotalVeryUnderweight/sum(TotalChildren))
names(Props4)[names(Props4)=="prop"] <- "PropVeryUnderweight"
n=Props4$TotalChildren
u=Props4$PropUnderweight
q=Props4$PropOverweight
p=Props4$PropObese
m=Props4$PropMorbidlyObese
s=Props4$PropSeverelyObese
v=Props4$PropVeryUnderweight
library(Hmisc)
propCIbinUnder<-binconf(x=Props4$TotalUnderweight, n=Props4$TotalChildren,alpha=.05, method="exact")
Props4$propCIbinUnderweightLower<-(propCIbinUnder[,2])
Props4$propCIbinUnderweightUpper<-(propCIbinUnder[,3])
propCIbinOver<-binconf(x=Props4$TotalOverweight, n=Props4$TotalChildren,alpha=.05, method="exact")
Props4$propCIbinOverweightLower<-(propCIbinOver[,2])
Props4$propCIbinOverweightUpper<-(propCIbinOver[,3])
propCIbinObese<-binconf(x=Props4$TotalObese, n=Props4$TotalChildren,alpha=.05, method="exact")
Props4$propCIbinObeseLower<-(propCIbinObese[,2])
Props4$propCIbinObeseUpper<-(propCIbinObese[,3])
propCIbinMorbid<-binconf(x=Props4$TotalMorbidlyObese, n=Props4$TotalChildren,alpha=.05, method="exact")
Props4$propCIbinMorbidlyObeseLower<-(propCIbinMorbid[,2])
Props4$propCIbinMorbidlyObeseUpper<-(propCIbinMorbid[,3])
propCIbinSevere<-binconf(x=Props4$TotalSeverelyObese, n=Props4$TotalChildren,alpha=.05, method="exact")
Props4$propCIbinSeverelyObeseLower<-(propCIbinSevere[,2])
Props4$propCIbinMorbidlyObeseUpper<-(propCIbinSevere[,3])
propCIbinVery<-binconf(x=Props4$TotalVeryUnderweight, n=Props4$TotalChildren,alpha=.05, method="exact")
Props4$propCIbinMorbidlyObeseLower<-(propCIbinVery[,2])
Props4$propCIbinMorbidlyObeseUpper<-(propCIbinVery[,3])
Props4$SEMBMI<-as.numeric(Props4$BMISD)/sqrt(n)
#WRITE AGE/GENDER SUMMARY DATA TO A CSV FILE (PER AGE AND GENDER GROUP:MEAN BMI, MEAN CI95%, MEDIAN BMI, TOTAL OBESE, TOTAL OVERWEIGHT, PROPORTION OBESE, PROPORTION OVERWEIGHT, PROP UPPER AND LOWER CI95s)
summaryfigures2014<-file(paste("summaryfigures2014.csv"), open="w")
cat("Gender", "SchoolYear","Children201617","NumberUnderweight","NumberOverweight","NumberObese","NumberMorbidlyObese","NumberSeverelyObese","NumberVeryUnderweight",
"MeanBMI","BMISD","BMISEM","MedianBMI",
"PropUnderweight","PropOverweight","PropObese","PropMorbidlyObese","PropSeverelyObese","PropVeryUnderweight",
"PropUwUpperCI","PropUwLowerCI","PropOwUpperCI","PropOwLowerCI",
"PropObUpperCI","PropObLowerCI", "PropMObUpperCI","PropMObLowerCI","\n", sep=",",file="summaryfigures2014.csv",append=TRUE)
for (n in 1:14){
cat((paste(Props4$Group.1[n])),(paste(Props4$Group.2[n])),(paste(Props4$TotalChildren[n])),(paste(Props4$TotalUnderweight[n])),(paste(Props4$TotalOverweight[n])),(paste(Props4$TotalObese[n])),(paste(Props4$TotalMorbidlyObese[n])),(paste(Props4$TotalSeverelyObese[n])),(paste(Props4$TotalVeryUnderweight[n])),
(paste(Props4$MeanBMI[n])),(paste(Props4$BMISD[n])),(paste(Props4$SEMBMI[n])),(paste(Props4$MedianBMI[n])),
(paste(Props4$PropUnderweight[n])),(paste(Props4$PropOverweight[n])),(paste(Props4$PropObese[n])),(paste(Props4$PropMorbidlyObese[n])),(paste(Props4$PropSeverelyObese[n])),(paste(Props4$PropVeryUnderweight[n])),
(paste(Props4$propCIbinUnderweightUpper[n])),(paste(Props4$propCIbinUnderweightLower[n])),
(paste(Props4$propCIbinOverweightUpper[n])),(paste(Props4$propCIbinOverweightLower[n])),
(paste(Props4$propCIbinObeseUpper[n])),(paste(Props4$propCIbinObeseLower[n])),(paste(Props4$propCIbinMorbidlyObeseUpper[n])),(paste(Props4$propCIbinMorbidlyObeseLower[n])),
"\n", file="summaryfigures2014.csv", sep=",", fill=FALSE, labels=NULL, append=TRUE)
}
NATIONAL
#WRITE AGE/GENDER SUMMARY DATA TO A CSV FILE (PER AGE AND GENDER GROUP:MEAN BMI, MEAN CI95%, MEDIAN BMI, TOTAL OBESE, TOTAL OVERWEIGHT, PROPORTION OBESE, PROPORTION OVERWEIGHT, PROP UPPER AND LOWER CI95s)
natfigures2016<-file(paste("natfigures2016.csv"), open="w")
cat("Gender", "SchoolYear","Children2016","NumberUnderweight","NumberOverweight","NumberObese","NumberMorbidlyObese",
"MeanBMI","BMISD","BMISEM","MedianBMI",
"PropUnderweight","PropOverweight","PropObese","PropMorbidlyObese",
"PropUwUpperCI","PropUwLowerCI","PropOwUpperCI","PropOwLowerCI",
"PropObUpperCI","PropObLowerCI", "PropMObUpperCI","PropMObLowerCI","\n", sep=",",file="natfigures2016.csv",append=TRUE)
for (n in 1:15){p
cat((paste(Props2$Group.1[n])),(paste(Props4$Group.2[n])),(paste(Props4$TotalChildren[n])),(paste(Props4$TotalUnderweight[n])),(paste(Props4$TotalOverweight[n])),(paste(Props4$TotalObese[n])),(paste(Props4$TotalMorbidlyObese[n])),
(paste(Props4$MeanBMI[n])),(paste(Props4$BMISD[n])),(paste(Props4$SEMBMI[n])),(paste(Props4$MedianBMI[n])),
(paste(Props4$PropUnderweight[n])),(paste(Props4$PropOverweight[n])),(paste(Props4$PropObese[n])),(paste(Props4$PropMorbidlyObese[n])),
(paste(Props4$propCIbinUnderweightUpper[n])),(paste(Props4$propCIbinUnderweightLower[n])),
(paste(Props4$propCIbinOverweightUpper[n])),(paste(Props4$propCIbinOverweightLower[n])),
(paste(Props4$propCIbinObeseUpper[n])),(paste(Props4$propCIbinObeseLower[n])),(paste(Props4$propCIbinMorbidlyObeseUpper[n])),(paste(Props4$propCIbinMorbidlyObeseLower[n])),
"\n", file="natfigures2016.csv", sep=",", fill=FALSE, labels=NULL, append=TRUE)
}
#AGGREGATE DATA BY SCHOOL
alldata<-read.table ("LMStable.csv",header=TRUE, sep=",")
names(alldata)[names(alldata)=="X"] <- "SDS_BMI"
#CREATE DATA SUBSET FOR THIS YEAR'S DATA
thisyear<-subset(alldata, alldata$AcademicYear=="2016/2017" & alldata$BMI<50)
attach(thisyear)
thisyear$Overweight<-ifelse(thisyear$SDS_BMI>=1.33,c("1"),("0"))
thisyear$Overweight<-as.numeric(Thisyear$Overweight)
thisyear$Obese<-ifelse(thisyear$SDS_BMI>=2,c("1"),("0"))
thisyear$Obese<-as.numeric(thisyear$Obese)
thisyear$mObese<-ifelse(thisyear$SDS_BMI>=3.33,c("1"),("0"))
thisyear$mObese<-as.numeric(thisyear$mObese)
thisyear$Underweight<-ifelse(thisyear$SDS_BMI<=-2,c("1"),("0"))
thisyear$Underweight<-as.numeric(thisyear$Underweight)
thisyear$<-as.numeric(thisyear$Underweight)
thisyear$ChildID<-"1"
thisyear$ChildID<-as.numeric(thisyear$ChildID)
schools1<-aggregate(thisyear$ChildID, by=list(thisyear$SchoolCode), FUN=sum)
names(schools1)[names(schools1)=="x"] <- "Children2016"
schools2<-aggregate(thisyear$Overweight, by=list(thisyear$SchoolCode), FUN=sum)
names(schools2)[names(schools2)=="x"] <- "Overweight"
schools3<-aggregate(thisyear$Obese, by=list(thisyear$SchoolCode), FUN=sum)
names(schools3)[names(schools3)=="x"] <- "Obese"
schools4<-aggregate(thisyear$mObese, by=list(thisyear$SchoolCode), FUN=sum)
names(schools4)[names(schools4)=="x"] <- "MorbidlyObese"
schools4<-aggregate(thisyear$mObese, by=list(thisyear$SchoolCode), FUN=sum)
names(schools4)[names(schools4)=="x"] <- "MorbidlyObese"
schools5<-aggregate(thisyear$Underweight, by=list(thisyear$SchoolCode), FUN=sum)
names(schools5)[names(schools5)=="x"] <- "Underweight"
summary1<-merge(schools1,schools2,all=TRUE, by=('Group.1'),)
summary2<-merge(summary1,schools3,all=TRUE, by=('Group.1'),)
summary3<-merge(summary2,schools4,all=TRUE, by=('Group.1'),)
summary4<-merge(summary3,schools5,all=TRUE, by=('Group.1'),)
library(plyr)
names(summary4)
Propssch<-ddply(summary4,.(Group.1),transform,prop=Overweight/sum(Children2016))
names(Propssch)[names(Propssch)=="prop"] <- "PropOverweight"
Propssch2<-ddply(Propssch,.(Group.1),transform,prop=Obese/sum(Children2016))
names(Propssch2)[names(Propssch2)=="prop"] <- "PropObese"
Propssch3<-ddply(Propssch2,.(Group.1),transform,prop=MorbidlyObese/sum(Children2016))
names(Propssch3)[names(Propssch3)=="prop"] <- "PropMorbidlyObese"
Propssch4<-ddply(Propssch3,.(Group.1),transform,prop=Underweight/sum(Children2016))
names(Propssch4)[names(Propssch4)=="prop"] <- "PropUnderweight"
n=Propssch4$Children2016
q=Propssch4$PropOverweight
p=Propssch4$PropObese
m=Propssch4$PropMorbidlyObese
u=Propssch4$PropUnderweight
propCIbinUnderweightsch<-binconf(x=Propssch4$Underweight, n=Propssch4$Children2016,alpha=.05, method="exact")
Propssch4$propCIbinUnderweightLower<-(propCIbinUnderweightsch[,2])
Propssch4$propCIbinUnderweightUpper<-(propCIbinUnderweightsch[,3])
propCIbinOverweight<-binconf(x=Propssch4$Overweight, n=Propssch4$Children2016,alpha=.05, method="exact")
Propssch4$propCIbinOverweightLower<-(propCIbinOverweight[,2])
Propssch4$propCIbinOverweightUpper<-(propCIbinOverweight[,3])
propCIbinObese<-binconf(x=Propssch4$Obese, n=Propssch4$Children2016,alpha=.05, method="exact")
Propssch4$propCIbinObeseLower<-(propCIbinObese[,2])
Propssch4$propCIbinObeseUpper<-(propCIbinObese[,3])
propCIbinMorbidlyObese<-binconf(x=Propssch4$MorbidlyObese, n=Propssch4$Children2016,alpha=.05, method="exact")
Propssch4$propCIbinMorbidlyObeseLower<-(propCIbinMorbidlyObese[,2])
Propssch4$propCIbinMorbidlyObeseUpper<-(propCIbinMorbidlyObese[,3])
#WRITE SCHOOL DATA TO A CSV FILE (PER SCHOOL:PUPILS MEASURED 2016, NO.UNDERWEIGHT, NO.OVERWEIGHT, NO.OBESE, NO.MORBIDLY OBESE, PROPORTION UNDERWEIGHT, PROPORTION OVERWEIGHT, PROPORTION OBESE, PROPORTION MORBIDLY OBESE, PROP UPPER AND LOWER CI95s)
schoolfigures2016<-file(paste("schoolfigures2016.csv"), open="w")
cat("School","Children2016","NumberUnderweight","NumberOverweight","NumberObese","NumberMorbidlyObese",
"PropUnderweight","PropOverweight","PropObese","PropMorbidlyObese",
"PropUnderwLowerCI","PropUnderwUpperCI","PropOverwLowerCI","PropOverwUpperCI","PropObLowerCI","PropObUpperCI","PropMorbidOwLowerCI","PropMorbidOwUpperCI","\n", sep=",",file="schoolfigures2016.csv",append=TRUE)
for (n in 1:27){p
cat((paste(Propssch4$Group.1[n])),(paste(Propssch4$Children2016[n])), (paste(Propssch4$Underweight[n])),(paste(Propssch4$Overweight[n])),(paste(Propssch4$Obese[n])),(paste(Propssch4$MorbidlyObese[n])),
(paste(Propssch4$PropUnderweight[n])),(paste(Propssch4$PropOverweight[n])),(paste(Propssch4$PropObese[n])),(paste(Propssch4$PropMorbidlyObese[n])),
(paste(Propssch4$propCIbinUnderweightUpper[n])),(paste(Propssch4$propCIbinUnderweightLower[n])),(paste(Propssch4$propCIbinOverweightUpper[n])),(paste(Propssch4$propCIbinOverweightLower[n])),(paste(Propssch4$propCIbinObeseUpper[n])),(paste(Propssch4$propCIbinObeseLower[n])),(paste(Propssch4$propCIbinMorbidlyObeseUpper[n])),(paste(Propssch4$propCIbinMorbidlyObeseUpper[n])),"\n", file="schoolfigures2016.csv", sep=",", fill=FALSE, labels=NULL, append=TRUE)
}
#AGGREGATE DATA BY SOCIAL DECILE (TEMPORARILY USING POSTCODE)
thisyear$ChildID<-as.numeric(thisyear$ChildID)
thisyear$Overweight<-as.numeric(thisyear$Overweight)
thisyear$Obese<-as.numeric(thisyear$Obese)
thisyear$mObese<-as.numeric(thisyear$mObese)
post1<-aggregate(thisyear$ChildID, by=list(thisyear$PostcodeDecile), FUN=sum)
names(post1)[names(post1)=="x"] <- "Children2016"
post2<-aggregate(thisyear$Overweight, by=list(thisyear$PostcodeDecile), FUN=sum)
names(post2)[names(post2)=="x"] <- "Overweight"
post3<-aggregate(thisyear$Obese, by=list(thisyear$PostcodeDecile), FUN=sum)
names(post3)[names(post3)=="x"] <- "Obese"
post4<-aggregate(thisyear$mObese, by=list(thisyear$PostcodeDecile), FUN=sum)
names(post4)[names(post4)=="x"] <- "MorbidlyObese"
post4<-aggregate(thisyear$mObese, by=list(thisyear$PostcodeDecile), FUN=sum)
names(post4)[names(post4)=="x"] <- "MorbidlyObese"
post5<-aggregate(thisyear$Underweight, by=list(thisyear$PostcodeDecile), FUN=sum)
names(post5)[names(post5)=="x"] <- "Underweight"
psummary1<-merge(post1,post2,all=TRUE, by=('Group.1'),)
psummary2<-merge(psummary1,post3,all=TRUE, by=('Group.1'),)
psummary3<-merge(psummary2,post4,all=TRUE, by=('Group.1'),)
psummary4<-merge(psummary3,post5,all=TRUE, by=('Group.1'),)
library(plyr)
names(psummary4)
Propsp<-ddply(psummary4,.(Group.1),transform,prop=Overweight/sum(Children2016))
names(Propsp)[names(Propsp)=="prop"] <- "PropOverweight"
Propsp2<-ddply(Propsp,.(Group.1),transform,prop=Obese/sum(Children2016))
names(Propsp2)[names(Propsp2)=="prop"] <- "PropObese"
Propsp3<-ddply(Propsp2,.(Group.1),transform,prop=MorbidlyObese/sum(Children2016))
names(Propsp3)[names(Propsp3)=="prop"] <- "PropMorbidlyObese"
Propsp4<-ddply(Propsp3,.(Group.1),transform,prop=Underweight/sum(Children2016))
names(Propsp4)[names(Propsp4)=="prop"] <- "PropUnderweight"
n=Propsp4$Children2016
q=Propsp4$PropOverweight
p=Propsp4$PropObese
m=Propsp4$PropMorbidlyObese
u=Propsp4$PropUnderweight
propCIbinUnderweightp<-binconf(x=Propsp4$Underweight, n=Propsp4$Children2016,alpha=.05, method="exact")
Propsp4$propCIbinUnderweightLower<-(propCIbinUnderweightp[,2])
Propsp4$propCIbinUnderweightUpper<-(propCIbinUnderweightp[,3])
propCIbinOverweightp<-binconf(x=Propsp4$Overweight, n=Propsp4$Children2016,alpha=.05, method="exact")
Propsp4$propCIbinOverweightLower<-(propCIbinOverweightp[,2])
Propsp4$propCIbinOverweightUpper<-(propCIbinOverweightp[,3])
propCIbinObese<-binconf(x=Propsp4$Obese, n=Propsp4$Children2016,alpha=.05, method="exact")
Propsp4$propCIbinObeseLower<-(propCIbinObese[,2])
Propsp4$propCIbinObeseUpper<-(propCIbinObese[,3])
propCIbinMorbidlyObese<-binconf(x=Propsp4$MorbidlyObese, n=Propsp4$Children2016,alpha=.05, method="exact")
Propsp4$propCIbinMorbidlyObeseLower<-(propCIbinMorbidlyObese[,2])
Propsp4$propCIbinMorbidlyObeseUpper<-(propCIbinMorbidlyObese[,3])
#WRITE SOCIAL DATA TO A CSV FILE (PER POSTCODE DECILE:PUPILS MEASURED 2016, NO.UNDERWEIGHT, NO.OVERWEIGHT, NO.OBESE, NO.MORBIDLY OBESE, PROPORTION UNDERWEIGHT, PROPORTION OVERWEIGHT, PROPORTION OBESE, PROPORTION MORBIDLY OBESE, PROP UPPER AND LOWER CI95s)
Socialfigures2016<-file(paste("socialfigures2016.csv"), open="w")
cat("PostcodeDecile","Children2016","NumberUnderweight","NumberOverweight","NumberObese","NumberMorbidlyObese",
"PropUnderweight","PropOverweight","PropObese","PropMorbidlyObese",
"PropUnderwLowerCI","PropUnderwUpperCI","PropOverwLowerCI","PropOverwUpperCI","PropObLowerCI","PropObUpperCI","PropMorbidOwLowerCI","PropMorbidOwUpperCI","\n", sep=",",file="socialfigures2016.csv",append=TRUE)
for (n in 1:11){p
cat((paste(Propsp4$Group.1[n])),(paste(Propsp4$Children2016[n])), (paste(Propsp4$Underweight[n])),(paste(Propsp4$Overweight[n])),(paste(Propsp4$Obese[n])),(paste(Propsp4$MorbidlyObese[n])),
(paste(Propsp4$PropUnderweight[n])),(paste(Propsp4$PropOverweight[n])),(paste(Propsp4$PropObese[n])),(paste(Propsp4$PropMorbidlyObese[n])),
(paste(Propsp4$propCIbinUnderweightUpper[n])),(paste(Propsp4$propCIbinUnderweightLower[n])),(paste(Propsp4$propCIbinOverweightUpper[n])),(paste(Propsp4$propCIbinOverweightLower[n])),(paste(Propsp4$propCIbinObeseUpper[n])),(paste(Propsp4$propCIbinObeseLower[n])),(paste(Propsp4$propCIbinMorbidlyObeseUpper[n])),(paste(Propsp4$propCIbinMorbidlyObeseLower[n])),"\n", file="socialfigures2016.csv", sep=",", fill=FALSE, labels=NULL, append=TRUE)
}
#OR FOR QUICK INDIVIDUAL PARAMETER QUERIES:
as.numeric(mergedtable$Overweight)
sum(BMI>=girls2016$OverweightBMI &girls2016$ageattest=="4")
mean(BMI[girls2016$ageattest=="4"])
sum(girls2016$ageattest=="4")