CHAMP-data-analysis/Check participating schools at master · HeatherARobinson/CHAMP-data-analysis · GitHub

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library(lubridate)
library(dplyr)
#CHECK FOR WEIGHT AND HEIGHT DATA ENTRY ERRORS.
#USE NHS 'VALIDATION OF CHILD MEASUREMENT PROGRAMME DATA' REPORT 2016 FOR ERROR REJECTION CUTOFFS
#CUTOFFS USED FOR RECEPTION AND YR6 ONLY-Update this
champ<-subset(champtable, champtable$HeightCM>=70 & champtable$HeightCM<=200 & champtable$WeightKG>=7 & champtable$WeightKG<=160)
s<-table(champtable$SchoolCode)
s = as.data.frame(s)
champ$SchoolCode<-ifelse(champ$SchoolCode %in% s$Var1,champ$SchoolCode,"NA")
attach(champ)
#Create additional derived variables
champ$BMI<-WeightKG/(HeightCM/100)^2
ndate1<-paste(DateOfBirth,"-01",sep=""); ndate1
ndate1<-(as.Date(ndate1))
ndate2<-paste(AssessmentDate,"-01",sep=""); ndate2
ndate2<-(as.Date(ndate2))
champ$ageattest<-floor(difftime(strptime(ndate2, format="%Y-%m-%d"),strptime(ndate1, format="%Y-%m-%d"),units="weeks")/52)
champ$ageattest<-as.integer(champ$ageattest)
attach(champ)
champ<-subset(champ, champ$ageattest<=11 & champ$ageattest>=4)
attach(champ)
levels(as.factor(champ$SchoolCode))
table(champ$ageattest)
setwd("c:/Users/mqbpjhr4/Documents/CHAMP")
champtable<-read.table("champ.csv", header=T,sep=",")
library(lubridate)
library(dplyr)
#CHECK FOR WEIGHT AND HEIGHT DATA ENTRY ERRORS.
#USE NHS 'VALIDATION OF CHILD MEASUREMENT PROGRAMME DATA' REPORT 2016 FOR ERROR REJECTION CUTOFFS
#CUTOFFS USED FOR RECEPTION AND YR6 ONLY-Update this
champ<-subset(champtable, champtable$HeightCM>=70 & champtable$HeightCM<=200 & champtable$WeightKG>=7 & champtable$WeightKG<=160)
s<-table(champtable$SchoolCode)
s = as.data.frame(s)
champ$SchoolCode<-ifelse(champ$SchoolCode %in% s$Var1,champ$SchoolCode,"NA")
attach(champ)
tab<-table(champ$SchoolCode)
tab
tab = as.data.frame(t)
tab = as.data.frame(tab)
head(tab)
schoolstable<-file(paste("schoolstable.csv"), open="w")
cat("School Code","Records")
ch<-table(champ$SchoolCode, champ$ChildID,fun=SUM)
ch<-table(champ$SchoolCode, champ$ChildID,FUN=count)
ch<-table(champ$SchoolCode, count(champ$ChildID))
ch<-table(champ$SchoolCode, levels(champ$ChildID))
ch<-table(champ$SchoolCode,champ$ChildID)
ch
ch<-table(champ$SchoolCode,nlevels(champ$ChildID))
ch<-table(champ$SchoolCode,nlevels(champ$ChildID),na.rm=TRUE)
DF2<-count(champ$ChildID~champ$SchoolCode)
DF2<-count(champ$ChildID,champ$SchoolCode)
DF2<-count(champ$ChildID,champ$SchoolCode)
library(plyr)
DF2<-count(champ$ChildID,champ$SchoolCode)
champ$ChildID<-as.factor(champ$ChildID)
champ$SchoolCode<-as.factor(champ$SchoolCode)
DF2<-count(champ$ChildID,champ$SchoolCode)
head(DF2)
DF2<-count(champ,c(ChildID,SchoolCode)
)
DF2<-count(champ,ChildID+SchoolCode)
DF2<-count(champ,SchoolCode)
DF2<-count(champ$ChildID,champ$SchoolCode)
head(DF2)
count(champ, c("SchoolCode", "ChildID"))
FAB<-count(champ, c("SchoolCode", "ChildID"))
head(FAB)
aggregate(freq ~ SchoolCodfe, data = fab, sum)
aggregate(freq ~ SchoolCode, data = fab, sum)
aggregate(freq ~ SchoolCode, data = FAB, sum)
FAB<-aggregate(freq ~ SchoolCode, data = FAB, sum)
head(FAB)
head(TAB)
head(tab)
names(tab)
names(tab)[1]<-"ChildID"
names(tab)[2]<-"Records"
names(tab)[1]<-"SchoolCode"
names(FAB)[2]<-"ChildIDs"
merge(FAB,tab,by=ChildID)
merge(FAB,tab,by="ChildID")
names(FAB)
names(tab)
merge(FAB,tab,by="SchoolCode")
schools<-merge(FAB,tab,by="SchoolCode")
head(schools)
head(schools,n=30)