gistfile1.txt

## QOL transformed scales
## PF_QOL
PF_QOL2<-PF_QOL
PF_QOL2<-ddply(PF_QOL2,.(Patientnr),.drop=FALSE,transform,baselinechange=pf2-pf2[1])
PF_QOL3<-PF_QOL
PF_QOL3<-ddply(PF_QOL3,.(Patientnr),.drop=FALSE,transform,change=pf2-lag(pf2))
PF_QOL$pf2_baselinechange<-PF_QOL2$baselinechange
PF_QOL$pf2_change<-PF_QOL3$change
PF_QOL$pf2_baselinechange[PF_QOL$time==0]<-NA
PF_QOL$pf2_change[PF_QOL$time==0]<-NA
PF_QOL
# Check visually if worked
g1<-ggplot(PF_QOL,aes(x=as.factor(time), y=pf2, group=as.factor(Patientnr)))+ geom_line() + geom_point() + facet_wrap(~Patientnr) + theme_bw()
g2<-ggplot(PF_QOL) + geom_bar(aes(as.factor(time), pf2_baselinechange), position = "dodge", stat = "summary", fun.y = "mean") + facet_wrap(~Patientnr) + theme_bw()
g3<-ggplot(PF_QOL) + geom_bar(aes(as.factor(time), pf2_change), position = "dodge", stat = "summary", fun.y = "mean") + facet_wrap(~Patientnr) + theme_bw()
grid.arrange(g1,g2,g3,ncol=3, top="PF_QOL Changes ")

## EF_QOL
EF_QOL2<-EF_QOL
EF_QOL2<-ddply(EF_QOL2,.(Patientnr),.drop=FALSE,transform,baselinechange=ef-ef[1])
EF_QOL3<-EF_QOL
EF_QOL3<-ddply(EF_QOL3,.(Patientnr),.drop=FALSE,transform,change=ef-lag(ef))
EF_QOL$ef_baselinechange<-EF_QOL2$baselinechange
EF_QOL$ef_change<-EF_QOL3$change
EF_QOL$ef_baselinechange[EF_QOL$time==0]<-NA
EF_QOL$ef_change[EF_QOL$time==0]<-NA
EF_QOL
# Check visually if worked
g1<-ggplot(EF_QOL,aes(x=as.factor(time), y=ef, group=as.factor(Patientnr)))+ geom_line() + geom_point() + facet_wrap(~Patientnr) + theme_bw()
g2<-ggplot(EF_QOL) + geom_bar(aes(as.factor(time), ef_baselinechange), position = "dodge", stat = "summary", fun.y = "mean") + facet_wrap(~Patientnr) + theme_bw()
g3<-ggplot(EF_QOL) + geom_bar(aes(as.factor(time), ef_change), position = "dodge", stat = "summary", fun.y = "mean") + facet_wrap(~Patientnr) + theme_bw()
grid.arrange(g1,g2,g3,ncol=3, top="EF_QOL Changes ")