R Notebook

overall.dat<-data.frame(atanh_out,alch_sub$total,dep_sub$total,swls_sub$total,rosenberg_sub$total,stress_sub$total)
p.alch.o<-ggplot(overall.dat, aes(x=alch_sub.total, y=atanh_out)) + geom_point(color="yellow3",pch=19,size=2)+geom_smooth(method=lm,color="yellow3",fill="yellow3",size=1.1)+theme_minimal()+labs(x="alchohol usage",y="overall average similarity")+theme(axis.title.x = element_text(face="bold"),axis.title.y = element_text(face="bold"))+stat_cor(method = "pearson",label.x.npc = "right",label.y=2.5)
  
p.dep.o<-ggplot(overall.dat, aes(x=dep_sub.total, y=atanh_out)) + geom_point(color="blue",pch=19,size=2)+geom_smooth(method=lm,color="blue",fill="blue",size=1.1)+theme_minimal()+labs(x="depression",y="overall average similarity")+theme(axis.title.x = element_text(face="bold"),axis.title.y = element_text(face="bold"))+stat_cor(method = "pearson",label.x.npc = "right",label.y=2.5)
p.stress.o<-ggplot(overall.dat, aes(x=stress_sub.total, y=atanh_out)) + geom_point(color="red",pch=19,size=2)+geom_smooth(method=lm,color="red",fill="red",size=1.1)+theme_minimal()+labs(x="stress",y="overall average similarity")+theme(axis.title.x = element_text(face="bold"),axis.title.y = element_text(face="bold"))+stat_cor(method = "pearson",label.x.npc = "right",label.y=2.5)
p.se.o<-ggplot(overall.dat, aes(x=rosenberg_sub.total, y=atanh_out)) + geom_point(color="green",pch=19,size=2)+geom_smooth(method=lm,color="green",fill="green",size=1.1)+theme_minimal()+labs(x="SE",y="soverall average similarity")+theme(axis.title.x = element_text(face="bold"),axis.title.y = element_text(face="bold"))+stat_cor(method = "pearson",label.x.npc = "left",label.y=2.5)
p.swls.o<-ggplot(overall.dat, aes(x=swls_sub.total, y=atanh_out)) + geom_point(color="purple",pch=19,size=2)+geom_smooth(method=lm,color="purple",fill="purple",size=1.1)+theme_minimal()+labs(x="SWLS",y="overall average similarity")+theme(axis.title.x = element_text(face="bold"),axis.title.y = element_text(face="bold"))+stat_cor(method = "pearson",label.x.npc = "left",label.y = 2.5)
grid.arrange(p.alch.o,p.dep.o,p.stress.o,p.se.o,p.swls.o,nrow=2,top=textGrob("Daily QC: Blue",gp=gpar(fontface="bold")))

all.dat<-data.frame(atanh_out,stress_sub$total,alch_sub$total,dep_sub$total,rosenberg_sub$total,swls_sub$total)
summary(lm(atanh_out~stress_sub.total+alch_sub.total+dep_sub.total+rosenberg_sub.total+swls_sub.total,data=all.dat))

Call:
lm(formula = atanh_out ~ stress_sub.total + alch_sub.total + 
    dep_sub.total + rosenberg_sub.total + swls_sub.total, data = all.dat)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.81951 -0.17662  0.00491  0.19238  0.91467 

Coefficients:
                      Estimate Std. Error t value Pr(>|t|)    
(Intercept)          1.3359458  0.2380126   5.613 2.44e-07 ***
stress_sub.total    -0.0184939  0.0059996  -3.083  0.00277 ** 
alch_sub.total      -0.0078478  0.0082610  -0.950  0.34481    
dep_sub.total       -0.0017084  0.0054843  -0.312  0.75618    
rosenberg_sub.total -0.0038574  0.0081202  -0.475  0.63598    
swls_sub.total      -0.0009843  0.0062860  -0.157  0.87594    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.295 on 85 degrees of freedom
Multiple R-squared:  0.2075,    Adjusted R-squared:  0.1609 
F-statistic: 4.452 on 5 and 85 DF,  p-value: 0.001191

p.alch<-ggplot(t, aes(x=alch_sub.total, y=similiarity)) + geom_point(color="yellow3",pch=19,size=2)+geom_smooth(method=lm,color="yellow3",fill="yellow3",size=1.1)+theme_minimal()+labs(x="alchohol usage",y="similarity between friend and sig other")+theme(axis.title.x = element_text(face="bold"),axis.title.y = element_text(face="bold"))+stat_cor(method = "pearson",label.x.npc = "right",label.y=2.5)
  
p.dep<-ggplot(t, aes(x=dep_sub.total, y=similiarity)) + geom_point(color="blue",pch=19,size=2)+geom_smooth(method=lm,color="blue",fill="blue",size=1.1)+theme_minimal()+labs(x="depression",y="similarity between friend and sig other")+theme(axis.title.x = element_text(face="bold"),axis.title.y = element_text(face="bold"))+stat_cor(method = "pearson",label.x.npc = "right",label.y=2.5)
p.stress<-ggplot(t, aes(x=stress_sub.total, y=similiarity)) + geom_point(color="red",pch=19,size=2)+geom_smooth(method=lm,color="red",fill="red",size=1.1)+theme_minimal()+labs(x="stress",y="similarity between friend and sig other")+theme(axis.title.x = element_text(face="bold"),axis.title.y = element_text(face="bold"))+stat_cor(method = "pearson",label.x.npc = "right",label.y=2.5)
p.se<-ggplot(t, aes(x=rosenberg_sub.total, y=similiarity)) + geom_point(color="green",pch=19,size=2)+geom_smooth(method=lm,color="green",fill="green",size=1.1)+theme_minimal()+labs(x="SE",y="ssimilarity between friend and sig other")+theme(axis.title.x = element_text(face="bold"),axis.title.y = element_text(face="bold"))+stat_cor(method = "pearson",label.x.npc = "left",label.y=2.5)
p.swls<-ggplot(t, aes(x=swls_sub.total, y=similiarity)) + geom_point(color="purple",pch=19,size=2)+geom_smooth(method=lm,color="purple",fill="purple",size=1.1)+theme_minimal()+labs(x="SWLS",y="similarity between friend and sig other")+theme(axis.title.x = element_text(face="bold"),axis.title.y = element_text(face="bold"))+stat_cor(method = "pearson",label.x.npc = "left",label.y = 2.5)
grid.arrange(p.alch,p.dep,p.stress,p.se,p.swls,nrow=2)