###################################################################################
# Replication file for "Experimental evidence for a pure collaboration effect" 	#
# author: Mary McGrath (mary.mcgrath@northwestern.edu) ORCID: 0000-0002-8437-4039 	#
# created: 10/25/2018	R version 3.3.2								#                      
 ###################################################################################

library(foreign)
library(sandwich)
library(pwr)

setwd("[insert directory where you've saved the datasets]")


dat<-read.dta("Collab_3-5.dta")


	## Proportion who give ##
#Experiment 1
Exp <-dat[dat$rd==3,]

#percent who give, separately-working
pctgS<-mean(Exp$gave[Exp$Collab==0], na.rm=T)*100
round(pctgS,1)
#percent who give, collaboratively-working
pctgC<-mean(Exp$gave[Exp$Collab==1], na.rm=T)*100
round(pctgC,1)
#collaboration effect
round(pctgC-pctgS,1)

(result<-prop.test(table(Exp$gave,Exp$Collab), correct=F))

#z
round(sqrt(result$statistic["X-squared"]),2)

#Cohen's h
h<-2*(asin(sqrt(mean(Exp$gave[Exp$Collab==1], na.rm=T))) - asin(sqrt(mean(Exp$gave[Exp$Collab==0], na.rm=T))))
round(h,3)



#Experiment 2
Exp <-dat[dat$rd==4,]

#percent who give, separately-working
pctgS<-mean(Exp$gave[Exp$Collab==0], na.rm=T)*100
round(pctgS,1)
#percent who give, collaboratively-working
pctgC<-mean(Exp$gave[Exp$Collab==1], na.rm=T)*100
round(pctgC,1)
#collaboration effect
round(pctgC-pctgS,1)

(result<-prop.test(table(Exp$gave,Exp$Collab), correct=F))

#z
round(sqrt(result$statistic["X-squared"]),2)

#Cohen's h
h<-2*(asin(sqrt(mean(Exp$gave[Exp$Collab==1], na.rm=T))) - asin(sqrt(mean(Exp$gave[Exp$Collab==0], na.rm=T))))
round(h,3)



#Experiment 3
Exp <-dat[dat$rd==5,]

#percent who give, separately-working
pctgS<-mean(Exp$gave[Exp$Collab==0], na.rm=T)*100
round(pctgS,1)
#percent who give, collaboratively-working
pctgC<-mean(Exp$gave[Exp$Collab==1], na.rm=T)*100
round(pctgC,1)
#collaboration effect
round(pctgC-pctgS,1)

(result<-prop.test(table(Exp$gave,Exp$Collab), correct=F))

#z
round(sqrt(result$statistic["X-squared"]),2)

#Cohen's h
h<-2*(asin(sqrt(mean(Exp$gave[Exp$Collab==1], na.rm=T))) - asin(sqrt(mean(Exp$gave[Exp$Collab==0], na.rm=T))))
round(h,3)





	## Proportion who split vs. $0 ##
#Experiment 1
Exp <-dat[dat$rd==3,]

#percent who split, separately-working
pctgS<-mean(Exp$half[Exp$Collab==0], na.rm=T)*100
round(pctgS,1)
#percent who split, collaboratively-working
pctgC<-mean(Exp$half[Exp$Collab==1], na.rm=T)*100
round(pctgC,1)
#collaboration effect
round(pctgC-pctgS,1)

(result<-prop.test(table(Exp$half,Exp$Collab), correct=F))

#z
round(sqrt(result$statistic["X-squared"]),2)

#Cohen's h
h<-2*(asin(sqrt(mean(Exp$half[Exp$Collab==1], na.rm=T))) - asin(sqrt(mean(Exp$half[Exp$Collab==0], na.rm=T))))
round(h,3)



#Experiment 2
Exp <-dat[dat$rd==4,]

#percent who split, separately-working
pctgS<-mean(Exp$half[Exp$Collab==0], na.rm=T)*100
round(pctgS,1)
#percent who split, collaboratively-working
pctgC<-mean(Exp$half[Exp$Collab==1], na.rm=T)*100
round(pctgC,1)
#collaboration effect
round(pctgC-pctgS,1)

(result<-prop.test(table(Exp$half,Exp$Collab), correct=F))

#z
round(sqrt(result$statistic["X-squared"]),2)

#Cohen's h
h<-2*(asin(sqrt(mean(Exp$half[Exp$Collab==1], na.rm=T))) - asin(sqrt(mean(Exp$half[Exp$Collab==0], na.rm=T))))
round(h,3)



#Experiment 3
Exp <-dat[dat$rd==5,]

#percent who split, separately-working
pctgS<-mean(Exp$half[Exp$Collab==0], na.rm=T)*100
round(pctgS,1)
#percent who split, collaboratively-working
pctgC<-mean(Exp$half[Exp$Collab==1], na.rm=T)*100
round(pctgC,1)
#collaboration effect
round(pctgC-pctgS,1)

(result<-prop.test(table(Exp$half,Exp$Collab), correct=F))

#z
round(sqrt(result$statistic["X-squared"]),2)

#Cohen's h
h<-2*(asin(sqrt(mean(Exp$half[Exp$Collab==1], na.rm=T))) - asin(sqrt(mean(Exp$half[Exp$Collab==0], na.rm=T))))
round(h,3)




	## Effort ##
given<-dat$given
Collab<-dat$Collab
effdiff<-dat$effdiff*10
effdiff2<-(dat$effdiff*10)^2
effdiff3<-(dat$effdiff*10)^3
effdiff4<-(dat$effdiff*10)^4
rd<-dat$rd
leveldiff<-dat$effdiff
leveldiff[dat$eff_level=="(+) large"]<-(-25.03)
leveldiff[dat$eff_level=="(+) small"]<-(-.03)
leveldiff[dat$eff_level=="(-) small"]<-.03
leveldiff[dat$eff_level=="(-) large"]<-25.03
leveldiff[dat$rd!=3]<-NA

data<-cbind(given,Collab,effdiff, effdiff2,effdiff3,effdiff4,rd, leveldiff)

reg<-lm(given ~ Collab + effdiff + effdiff2 + as.factor(rd), data=dat)
summary(reg)

#Cohen's d, collaboration
round(coef(reg)["Collab"]/sqrt(var(dat$given)),3)

#Cohen's d, effort
round(coef(reg)["effdiff"]/sqrt(var(dat$given)),3)

reg<-lm(given ~ Collab + effdiff + Collab*effdiff + effdiff2 + as.factor(rd), data=dat)
summary(reg)




	## Affinity ##
#within-subject change, before to after treatment
round(mean(dat$affincrease, na.rm=T),2)
round(sqrt(var(dat$affincrease, na.rm=T)),2)
t.test(affincrease ~ Collab, data=dat)
#Cohen's d 
round((mean(dat$affincrease[dat$Collab==1], na.rm=T) - mean(dat$affincrease[dat$Collab==0], na.rm=T))/sqrt(var(dat$affincrease, na.rm=T)),3)


#replication, asking only after treatment
dat2<-read.dta("Collab_affin_St12.dta")
t.test(affinity ~ Collab, data=dat2)
#Cohen's d 
round((mean(dat2$affinity[dat2$Collab==1], na.rm=T) - mean(dat2$affinity[dat2$Collab==0], na.rm=T))/sqrt(var(dat2$affinity, na.rm=T)),3)




	## Primary Reason ##
#relative to reciprocity
debt<-rep(NA, length(dat$primary))
debt[dat$primary=="recipr"]<-0
debt[dat$primary=="debt"]<-1

z<-qnorm(1-(.05/2))
summary(reg<-lm(debt~dat$Collab))
rse<-sqrt(diag(vcovHC(reg, type="HC0")))

#lower CI
round(reg$coeff[2] - z*rse[2],3)
#upper CI
round(reg$coeff[2] + z*rse[2],3)

#Cohen's h
round(2*(asin(sqrt(mean(debt[Exp$Collab==1], na.rm=T))) - asin(sqrt(mean(debt[Exp$Collab==0], na.rm=T)))),3)






	## Experiment 4 ##
Exp <- read.dta("Collab_Exp4.dta")

#percent who give, separately-working
pctgS<-mean(Exp$gave[Exp$collab==0], na.rm=T)*100
round(pctgS,1)
#percent who give, collaboratively-working
pctgC<-mean(Exp$gave[Exp$collab==1], na.rm=T)*100
round(pctgC,1)
#collaboration effect
round(pctgC-pctgS,1)

(result<-prop.test(table(Exp$gave,Exp$collab), correct=T))

#Cohen's h
h<-2*(asin(sqrt(mean(Exp$gave[Exp$collab==1], na.rm=T))) - asin(sqrt(mean(Exp$gave[Exp$collab==0], na.rm=T))))
round(h,3)



#percent who split, separately-working
pctgS<-mean(Exp$half[Exp$collab==0], na.rm=T)*100
round(pctgS,1)
#percent who split, collaboratively-working
pctgC<-mean(Exp$half[Exp$collab==1], na.rm=T)*100
round(pctgC,1)
#collaboration effect
round(pctgC-pctgS,1)

(result<-prop.test(table(Exp$half,Exp$collab), correct=T))

#Cohen's h
h<-2*(asin(sqrt(mean(Exp$half[Exp$collab==1], na.rm=T))) - asin(sqrt(mean(Exp$half[Exp$collab==0], na.rm=T))))
round(h,3)





	## Supplementary Information ##
#Table S1
summary(lm(given ~ Collab + norm + Collab*norm + as.factor(rd), data=dat))