##################################################################################################################
#update path!
setwd("C:/....")


library(foreign)


dat = as.data.frame(read.spss("EMAAge_HRQOL_peerj.sav", use.value.labels=T))
#
dat0 = subset(dat, select = c(dropout, study_center, Sex, Age, CASMIN, migration, livingsituation, Personshousehold, proxy,
                              Pre_fracture_dependency, Fracture_type, Charlson_commorbity_index, polypharmacy, Social_support,
                              subjective_need, Surgery, ICU_episode, Referral_to_rehabilitation_facility, Malnutrition,  
                              PHQ_4, OHS, 
                              EQ5Dindex_diff, vas_diff, EQ5Dindex, EQ5Dindex_FU, vas_retro_bl, vas_today_a, Died))


#####################################################################################################
table(dat0$study_center)
dat0$study_center <- relevel(dat0$study_center, ref = "University hospital")
table(dat0$Sex)
dat0$Sex <- relevel(dat0$Sex, ref = "female")
table(dat0$Age)
table(dat0$CASMIN)
table(dat0$migration)
table(dat0$livingsituation)
####
table(dat0$Personshousehold)
levels(dat0$Personshousehold)[levels(dat0$Personshousehold)=="I don't know"] <- NA
levels(dat0$Personshousehold) <- c("Own home alone", "Own home with others", "Other")
dat0$Personshousehold[dat0$livingsituation=="Facility/other"] <- "Other"
dat0$Personshousehold <- relevel(dat0$Personshousehold, ref = "Own home with others")
table(dat0$proxy)
table(dat0$Pre_fracture_dependency)
####
table(dat0$Fracture_type)
levels(dat0$Fracture_type)[levels(dat0$Fracture_type)=="Pertrochanteric fracture" | levels(dat0$Fracture_type)=="Subtrochanteric fracture"] <- "Per- or Subtrochanteric fracture"
#### Exclusion of fracture type "Periprosthetic fracture", because only 5 times
dat0 <- dat0[!(dat0$Fracture_type=="Periprosthetic fracture"),]
levels(dat0$Fracture_type)[levels(dat0$Fracture_type)=="Periprosthetic fracture"] <- NA
table(dat0$Charlson_commorbity_index)
dat0$Charlson_commorbity_index_cat <- dat0$Charlson_commorbity_index
dat0$Charlson_commorbity_index_cat[dat0$Charlson_commorbity_index_cat>2] <- "3+"
dat0$Charlson_commorbity_index_cat <- as.factor(dat0$Charlson_commorbity_index_cat)
levels(dat0$Charlson_commorbity_index_cat) <- c("0","1", "2", "3+")
table(dat0$Charlson_commorbity_index_cat)
table(dat0$polypharmacy)
table(dat0$Social_support)
levels(dat0$Social_support)[levels(dat0$Social_support)=="I don't know / n.a."] <- NA
levels(dat0$Social_support)[levels(dat0$Social_support)=="None" | levels(dat0$Social_support)=="1 or 2 people"] <- "0 - 2 people"
table(dat0$subjective_need)
table(dat0$Surgery)
#### Exclusion of patients without OP
dat0 <- dat0[!(dat0$Surgery=="No surgery"),]
levels(dat0$Surgery)[levels(dat0$Surgery)=="No surgery"] <- NA
dat0$Surgery <- relevel(dat0$Surgery, ref="Internal Fixation")
table(dat0$ICU_episode)
levels(dat0$ICU_episode)[levels(dat0$ICU_episode)=="n.a."] <- NA
dat0$ICU_episode <- relevel(dat0$ICU_episode, ref = "no")
table(dat0$Referral_to_rehabilitation_facility)
dat0$Referral_to_rehabilitation_facility <- relevel(dat0$Referral_to_rehabilitation_facility, ref = "yes")
table(dat0$Malnutrition)
table(dat0$PHQ_4)
dat0$PHQ_4_cat[dat0$PHQ_4>5] <- ">=6" 
dat0$PHQ_4_cat[dat0$PHQ_4<6] <- "<6"
dat0$PHQ_4_cat <- as.factor(dat0$PHQ_4_cat)
table(dat0$PHQ_4_cat)
table(dat0$OHS)
#####-------------- Exclusion of patients that died -----------------#####
table(dat0$Died)
dat0 <- dat0[dat0$Died=="no",]

#### dependent variables
table(dat0$EQ5Dindex_diff)
table(dat0$vas_diff)
table(dat0$EQ5Dindex)
dat0$EQ5Dindex[dat0$EQ5Dindex==9] <- NA
table(dat0$EQ5Dindex_FU)
dat0$EQ5Dindex_FU[dat0$EQ5Dindex_FU==9] <- NA
table(dat0$vas_retro_bl)
table(dat0$vas_today_a)

head(dat0)
summary(dat0)

## delete variable "Died", dataset is reduced to living patients
dat1 = subset(dat0, select = c(study_center, Sex, Age, CASMIN, migration, Personshousehold, proxy,
                              Pre_fracture_dependency, Fracture_type, Charlson_commorbity_index_cat, polypharmacy, Social_support,
                              subjective_need, Surgery, ICU_episode, Referral_to_rehabilitation_facility, Malnutrition, PHQ_4_cat, OHS,
                              EQ5Dindex_diff, vas_diff, EQ5Dindex, EQ5Dindex_FU, vas_retro_bl, vas_today_a))


######################################################################################################################
############################## Datasets for sensitivity analyses ##################################################

### without Dropouts ###
table(dat0$dropout)
dat2 <- subset(dat0, select = c(dropout, study_center, Sex, Age, CASMIN, migration, Personshousehold, proxy,
                                Pre_fracture_dependency, Fracture_type, Charlson_commorbity_index_cat, polypharmacy, Social_support,
                                subjective_need, Surgery, ICU_episode, Referral_to_rehabilitation_facility, Malnutrition, PHQ_4_cat, OHS,
                                EQ5Dindex_diff, vas_diff, EQ5Dindex, EQ5Dindex_FU, vas_retro_bl, vas_today_a))

dat_withoutDropout <- dat2[dat2$dropout=="No dropout",]
dat_withoutDropout <- subset(dat_withoutDropout, select = c(study_center, Sex, Age, CASMIN, migration, Personshousehold, proxy,
                                                            Pre_fracture_dependency, Fracture_type, Charlson_commorbity_index_cat, polypharmacy, Social_support,
                                                            subjective_need, Surgery, ICU_episode, Referral_to_rehabilitation_facility, Malnutrition, PHQ_4_cat, OHS,
                                                            EQ5Dindex_diff, vas_diff, EQ5Dindex, EQ5Dindex_FU, vas_retro_bl, vas_today_a))

### only patients age 65+  ###
dat_65 <- dat1[dat1$Age>64,]