gistfile1.txt

try<-qol_combined%>%dplyr::select(Patientnr,variable,time,value)%>%
  dplyr::filter(variable=="QOL_1_"|variable=="QOL_2_"|variable=="QOL_3_")%>%
  dplyr::group_by(Patientnr,time)%>%arrange(Patientnr, time);head(try)
g1<-ggplot(try, aes(x=as.factor(time),y=as.factor(variable),fill=as.factor(value)))+geom_tile(colour="white",size=0.25, na.rm=TRUE)+
  labs(x="",y="")+scale_y_discrete(expand=c(0,0))+
  scale_fill_viridis(discrete = TRUE, option="magma", direction = -1 )+
  facet_wrap(~Patientnr)+
  theme_grey(base_size=10)+marc_discrete # shows that, although missing across patients and across time, there are no missing within a form. Hence, I expect to have pf2 values! 
PF_QOL<-try%>%
  dplyr::summarise(pf = sum(value), pfsum = 12-pf) %>%
  dplyr::mutate(pf2 = case_when(
    pfsum>0 & pfsum<6 ~ pfsum*100/15,
    pfsum == 6        ~ 7*100/15,
    pfsum == 7        ~ 9*100/15,
    pfsum == 8        ~ 11*100/15,
    pfsum == 9        ~ 14*100/15,
    TRUE ~ 0));head(PF_QOL)
PF_QOL$pf2<-ifelse(PF_QOL$pf2==0, NA, PF_QOL$pf2)
head(PF_QOL);histogram(PF_QOL$pf2)
g3<-ggplot(PF_QOL,aes(x=as.factor(time), y=pf2, group=as.factor(Patientnr)))+ geom_line() + geom_point() + facet_wrap(~Patientnr) + theme_bw()
g4<-ggplot(PF_QOL, aes(x=as.factor(time),y=pf2))+geom_boxplot()+theme_bw()
g2<-ggplot(PF_QOL,aes(x=as.factor(time),y=as.factor(Patientnr),fill=pf2))+geom_tile(colour="white",size=0.25, na.rm=TRUE)+
  labs(x="",y="")+scale_y_discrete(expand=c(0,0))+
  scale_fill_viridis(discrete = FALSE, option="mako", direction = -1 )+
  theme_grey(base_size=10)+marc_discrete
grid.arrange(g1,g2,g3,g4,ncol=4, top="Physical Functioning")