pdf(file="Figure_4.pdf",width=12,height=8)
par(mar=c(4.1,5,4,1),fig=c(0,.375,0,1))


################# LOAD PACKAGES
library(rstan)
library(rethinking)
library(parallel)
library(binom)

################# LOAD DATA

dataset <- read.csv("Data__current_study.csv")

#################

predict.values <- "NO"

################# SELECT MODEL

model = Model_5

post <- extract.samples(model)

################# GENERAL PARAMETERS

col0= 	rgb(0,0,0,255,max=255)
shade0= rgb(0,0,0,70,max=255) 
col1= 	rgb(255,0,0,255,max=255)
shade1= rgb(255,0,0,70,max=255) 
col2= 	rgb(0,0,255,255,max=255)
shade2= rgb(0,0,255,70,max=255) 
col3= 	rgb(0,153,0,255,max=255)
shade3= rgb(0,153,0,70,max=255) 
col4= 	rgb(204,102,0,255,max=255)
shade4= rgb(204,102,0,70,max=255) 
col5= 	rgb(127,0,255,255,max=255)
shade5= rgb(127,0,255,70,max=255) 
col6= 	rgb(153,150,76,255,max=255)
shade6= rgb(153,150,76,70,max=255) 
col7= 	rgb(216,5,202,255,max=255)
shade7= rgb(75,0,153,70,max=255) 
col8= 	rgb(100,100,100,255,max=255)
shade8= rgb(100,100,100,70,max=255) 

length=30	# Length of vector of predictions, i.e. how many predictions are plotted per line


age.seq0a <- seq( from=min(dataset[dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c), to=max(dataset[dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c) , length.out=length)
age.seq1a <- seq( from=min(dataset[dataset$fieldid==1 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c), to=max(dataset[dataset$fieldid==1 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c) , length.out=length)
age.seq2a <- seq( from=min(dataset[dataset$fieldid==2 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c), to=max(dataset[dataset$fieldid==2 & dataset$CONDITION_1_1yes==1 & dataset$CONDITION_2_1yes==0,]$age_c) , length.out=length)
age.seq3a <- seq( from=min(dataset[dataset$fieldid==3 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c), to=max(dataset[dataset$fieldid==3 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c) , length.out=length)
age.seq4a <- seq( from=min(dataset[dataset$fieldid==4 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c), to=max(dataset[dataset$fieldid==4 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c) , length.out=length)
age.seq5a <- seq( from=min(dataset[dataset$fieldid==5 & dataset$CONDITION_1_1yes==1 & dataset$CONDITION_2_1yes==0,]$age_c), to=max(dataset[dataset$fieldid==5 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c) , length.out=length)
age.seq6a <- seq( from=min(dataset[dataset$fieldid==6 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c), to=max(dataset[dataset$fieldid==6 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c) , length.out=length)

age.seq0b <- seq( from=min(dataset[dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c), to=max(dataset[dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c) , length.out=length)
age.seq1b <- seq( from=min(dataset[dataset$fieldid==1 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==1,]$age_c), to=max(dataset[dataset$fieldid==1 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c) , length.out=length)
age.seq2b <- seq( from=min(dataset[dataset$fieldid==2 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==1,]$age_c), to=max(dataset[dataset$fieldid==2 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==1,]$age_c) , length.out=length)
age.seq3b <- seq( from=min(dataset[dataset$fieldid==3 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==1,]$age_c), to=max(dataset[dataset$fieldid==3 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c) , length.out=length)
age.seq4b <- seq( from=min(dataset[dataset$fieldid==4 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c), to=max(dataset[dataset$fieldid==4 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c) , length.out=length)
age.seq5b <- seq( from=min(dataset[dataset$fieldid==5 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c), to=max(dataset[dataset$fieldid==5 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c) , length.out=length)
age.seq6b <- seq( from=min(dataset[dataset$fieldid==6 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==0,]$age_c), to=max(dataset[dataset$fieldid==6 & dataset$CONDITION_1_1yes==0 & dataset$CONDITION_2_1yes==1,]$age_c) , length.out=length)



################# EXTRA PARAMETERS 

aid=rep(1,length)
aid_zeros=matrix(0,10000,length(unique(dataset$aid)))
fieldid_zeros=matrix(0,10000,length(unique(dataset$fieldid)))

CONDITION_altruistic_1yes = rep(1,length)

################# EXTRA PARAMETERS 





################# ESTIMATES FOR AVERAGE SITE
age_c=age.seq1a
age_2c=age_c^2	
CONDITION_1_1yes = rep(1,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_1_1yes) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_1_1yes*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        b_age_c_X_CONDITION_1_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes
)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_1_1yes[i]))
pred0a_prime <- apply(pred.raw , 2 , mean)
pred.PI0a_prime <- apply( pred.raw , 2 , PI)



CONDITION_2_1yes = rep(1,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_2_1yes) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_2_1yes*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        b_age_c_X_CONDITION_2_1yes*age_c*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes 
)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_2_1yes[i]))
pred0b_prime <- apply(pred.raw , 2 , mean)
pred.PI0b_prime <- apply( pred.raw , 2 , PI)




################# ESTIMATES FOR BERLIN
fieldid <- rep(1, length)
age_c=age.seq1a
age_2c=age_c^2	
CONDITION_1_1yes = rep(1,length)
CONDITION_2_1yes = rep(0,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_1_1yes, CONDITION_2_1yes, fieldid) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_1_1yes*CONDITION_1_1yes +
        b_CONDITION_2_1yes*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        b_age_c_X_CONDITION_1_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        b_age_c_X_CONDITION_2_1yes*age_c*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes +
        v_fieldid_Intercept[,fieldid] +
        v_fieldid_CONDITION_altruistic_1yes[,fieldid]*CONDITION_altruistic_1yes +
        v_fieldid_age_c[,fieldid]*age_c +
        v_fieldid_CONDITION_1_1yes[,fieldid]*CONDITION_1_1yes +
        v_fieldid_CONDITION_2_1yes[,fieldid]*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c[,fieldid]*CONDITION_altruistic_1yes*age_c +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        v_fieldid_age_c_X_CONDITION_1_1yes[,fieldid]*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        v_fieldid_age_c_X_CONDITION_2_1yes[,fieldid]*age_c*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes

)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_1_1yes[i], CONDITION_2_1yes[i], fieldid[i]))
pred1a_prime <- apply(pred.raw , 2 , mean)
pred.PI1a_prime <- apply( pred.raw , 2 , PI)



CONDITION_1_1yes = rep(0,length)
CONDITION_2_1yes = rep(1,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_1_1yes, CONDITION_2_1yes, fieldid) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_1_1yes*CONDITION_1_1yes +
        b_CONDITION_2_1yes*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        b_age_c_X_CONDITION_1_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        b_age_c_X_CONDITION_2_1yes*age_c*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes +
        v_fieldid_Intercept[,fieldid] +
        v_fieldid_CONDITION_altruistic_1yes[,fieldid]*CONDITION_altruistic_1yes +
        v_fieldid_age_c[,fieldid]*age_c +
        v_fieldid_CONDITION_1_1yes[,fieldid]*CONDITION_1_1yes +
        v_fieldid_CONDITION_2_1yes[,fieldid]*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c[,fieldid]*CONDITION_altruistic_1yes*age_c +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        v_fieldid_age_c_X_CONDITION_1_1yes[,fieldid]*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        v_fieldid_age_c_X_CONDITION_2_1yes[,fieldid]*age_c*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes

)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_1_1yes[i], CONDITION_2_1yes[i], fieldid[i]))
pred1b_prime <- apply(pred.raw , 2 , mean)
pred.PI1b_prime <- apply( pred.raw , 2 , PI)





################# ESTIMATES FOR LA PLATA
fieldid <- rep(2, length)
age_c=age.seq2a
age_2c=age_c^2	
CONDITION_1_1yes = rep(1,length)
CONDITION_2_1yes = rep(0,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_1_1yes, CONDITION_2_1yes, fieldid) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_1_1yes*CONDITION_1_1yes +
        b_CONDITION_2_1yes*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        b_age_c_X_CONDITION_1_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        b_age_c_X_CONDITION_2_1yes*age_c*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes +
        v_fieldid_Intercept[,fieldid] +
        v_fieldid_CONDITION_altruistic_1yes[,fieldid]*CONDITION_altruistic_1yes +
        v_fieldid_age_c[,fieldid]*age_c +
        v_fieldid_CONDITION_1_1yes[,fieldid]*CONDITION_1_1yes +
        v_fieldid_CONDITION_2_1yes[,fieldid]*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c[,fieldid]*CONDITION_altruistic_1yes*age_c +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        v_fieldid_age_c_X_CONDITION_1_1yes[,fieldid]*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        v_fieldid_age_c_X_CONDITION_2_1yes[,fieldid]*age_c*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes

)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_1_1yes[i], CONDITION_2_1yes[i], fieldid[i]))
pred2a_prime <- apply(pred.raw , 2 , mean)
pred.PI2a_prime <- apply( pred.raw , 2 , PI)



CONDITION_1_1yes = rep(0,length)
CONDITION_2_1yes = rep(1,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_1_1yes, CONDITION_2_1yes, fieldid) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_1_1yes*CONDITION_1_1yes +
        b_CONDITION_2_1yes*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        b_age_c_X_CONDITION_1_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        b_age_c_X_CONDITION_2_1yes*age_c*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes +
        v_fieldid_Intercept[,fieldid] +
        v_fieldid_CONDITION_altruistic_1yes[,fieldid]*CONDITION_altruistic_1yes +
        v_fieldid_age_c[,fieldid]*age_c +
        v_fieldid_CONDITION_1_1yes[,fieldid]*CONDITION_1_1yes +
        v_fieldid_CONDITION_2_1yes[,fieldid]*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c[,fieldid]*CONDITION_altruistic_1yes*age_c +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        v_fieldid_age_c_X_CONDITION_1_1yes[,fieldid]*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        v_fieldid_age_c_X_CONDITION_2_1yes[,fieldid]*age_c*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes

)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_1_1yes[i], CONDITION_2_1yes[i], fieldid[i]))
pred2b_prime <- apply(pred.raw , 2 , mean)
pred.PI2b_prime <- apply( pred.raw , 2 , PI)





################# ESTIMATES FOR PHOENIX
fieldid <- rep(3, length)
age_c=age.seq3a
age_2c=age_c^2	
CONDITION_1_1yes = rep(1,length)
CONDITION_2_1yes = rep(0,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_1_1yes, CONDITION_2_1yes, fieldid) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_1_1yes*CONDITION_1_1yes +
        b_CONDITION_2_1yes*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        b_age_c_X_CONDITION_1_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        b_age_c_X_CONDITION_2_1yes*age_c*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes +
        v_fieldid_Intercept[,fieldid] +
        v_fieldid_CONDITION_altruistic_1yes[,fieldid]*CONDITION_altruistic_1yes +
        v_fieldid_age_c[,fieldid]*age_c +
        v_fieldid_CONDITION_1_1yes[,fieldid]*CONDITION_1_1yes +
        v_fieldid_CONDITION_2_1yes[,fieldid]*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c[,fieldid]*CONDITION_altruistic_1yes*age_c +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        v_fieldid_age_c_X_CONDITION_1_1yes[,fieldid]*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        v_fieldid_age_c_X_CONDITION_2_1yes[,fieldid]*age_c*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes

)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_1_1yes[i], CONDITION_2_1yes[i], fieldid[i]))
pred3a_prime <- apply(pred.raw , 2 , mean)
pred.PI3a_prime <- apply( pred.raw , 2 , PI)



CONDITION_1_1yes = rep(0,length)
CONDITION_2_1yes = rep(1,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_1_1yes, CONDITION_2_1yes, fieldid) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_1_1yes*CONDITION_1_1yes +
        b_CONDITION_2_1yes*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        b_age_c_X_CONDITION_1_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        b_age_c_X_CONDITION_2_1yes*age_c*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes +
        v_fieldid_Intercept[,fieldid] +
        v_fieldid_CONDITION_altruistic_1yes[,fieldid]*CONDITION_altruistic_1yes +
        v_fieldid_age_c[,fieldid]*age_c +
        v_fieldid_CONDITION_1_1yes[,fieldid]*CONDITION_1_1yes +
        v_fieldid_CONDITION_2_1yes[,fieldid]*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c[,fieldid]*CONDITION_altruistic_1yes*age_c +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        v_fieldid_age_c_X_CONDITION_1_1yes[,fieldid]*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        v_fieldid_age_c_X_CONDITION_2_1yes[,fieldid]*age_c*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes

)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_1_1yes[i], CONDITION_2_1yes[i], fieldid[i]))
pred3b_prime <- apply(pred.raw , 2 , mean)
pred.PI3b_prime <- apply( pred.raw , 2 , PI)






################# ESTIMATES FOR PUNE
fieldid <- rep(4, length)
age_c=age.seq4a
age_2c=age_c^2	
CONDITION_1_1yes = rep(1,length)
CONDITION_2_1yes = rep(0,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_1_1yes, CONDITION_2_1yes, fieldid) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_1_1yes*CONDITION_1_1yes +
        b_CONDITION_2_1yes*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        b_age_c_X_CONDITION_1_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        b_age_c_X_CONDITION_2_1yes*age_c*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes +
        v_fieldid_Intercept[,fieldid] +
        v_fieldid_CONDITION_altruistic_1yes[,fieldid]*CONDITION_altruistic_1yes +
        v_fieldid_age_c[,fieldid]*age_c +
        v_fieldid_CONDITION_1_1yes[,fieldid]*CONDITION_1_1yes +
        v_fieldid_CONDITION_2_1yes[,fieldid]*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c[,fieldid]*CONDITION_altruistic_1yes*age_c +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        v_fieldid_age_c_X_CONDITION_1_1yes[,fieldid]*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        v_fieldid_age_c_X_CONDITION_2_1yes[,fieldid]*age_c*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes

)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_1_1yes[i], CONDITION_2_1yes[i], fieldid[i]))
pred4a_prime <- apply(pred.raw , 2 , mean)
pred.PI4a_prime <- apply( pred.raw , 2 , PI)



CONDITION_1_1yes = rep(0,length)
CONDITION_2_1yes = rep(1,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_1_1yes, CONDITION_2_1yes, fieldid) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_1_1yes*CONDITION_1_1yes +
        b_CONDITION_2_1yes*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        b_age_c_X_CONDITION_1_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        b_age_c_X_CONDITION_2_1yes*age_c*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes +
        v_fieldid_Intercept[,fieldid] +
        v_fieldid_CONDITION_altruistic_1yes[,fieldid]*CONDITION_altruistic_1yes +
        v_fieldid_age_c[,fieldid]*age_c +
        v_fieldid_CONDITION_1_1yes[,fieldid]*CONDITION_1_1yes +
        v_fieldid_CONDITION_2_1yes[,fieldid]*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c[,fieldid]*CONDITION_altruistic_1yes*age_c +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        v_fieldid_age_c_X_CONDITION_1_1yes[,fieldid]*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        v_fieldid_age_c_X_CONDITION_2_1yes[,fieldid]*age_c*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes

)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_1_1yes[i], CONDITION_2_1yes[i], fieldid[i]))
pred4b_prime <- apply(pred.raw , 2 , mean)
pred.PI4b_prime <- apply( pred.raw , 2 , PI)










################# ESTIMATES FOR SHUAR
fieldid <- rep(5, length)
age_c=age.seq5a
age_2c=age_c^2	
CONDITION_1_1yes = rep(1,length)
CONDITION_2_1yes = rep(0,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_1_1yes, CONDITION_2_1yes, fieldid) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_1_1yes*CONDITION_1_1yes +
        b_CONDITION_2_1yes*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        b_age_c_X_CONDITION_1_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        b_age_c_X_CONDITION_2_1yes*age_c*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes +
        v_fieldid_Intercept[,fieldid] +
        v_fieldid_CONDITION_altruistic_1yes[,fieldid]*CONDITION_altruistic_1yes +
        v_fieldid_age_c[,fieldid]*age_c +
        v_fieldid_CONDITION_1_1yes[,fieldid]*CONDITION_1_1yes +
        v_fieldid_CONDITION_2_1yes[,fieldid]*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c[,fieldid]*CONDITION_altruistic_1yes*age_c +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        v_fieldid_age_c_X_CONDITION_1_1yes[,fieldid]*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        v_fieldid_age_c_X_CONDITION_2_1yes[,fieldid]*age_c*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes

)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_1_1yes[i], CONDITION_2_1yes[i], fieldid[i]))
pred5a_prime <- apply(pred.raw , 2 , mean)
pred.PI5a_prime <- apply( pred.raw , 2 , PI)



CONDITION_1_1yes = rep(0,length)
CONDITION_2_1yes = rep(1,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_1_1yes, CONDITION_2_1yes, fieldid) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_1_1yes*CONDITION_1_1yes +
        b_CONDITION_2_1yes*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        b_age_c_X_CONDITION_1_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        b_age_c_X_CONDITION_2_1yes*age_c*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes +
        v_fieldid_Intercept[,fieldid] +
        v_fieldid_CONDITION_altruistic_1yes[,fieldid]*CONDITION_altruistic_1yes +
        v_fieldid_age_c[,fieldid]*age_c +
        v_fieldid_CONDITION_1_1yes[,fieldid]*CONDITION_1_1yes +
        v_fieldid_CONDITION_2_1yes[,fieldid]*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c[,fieldid]*CONDITION_altruistic_1yes*age_c +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        v_fieldid_age_c_X_CONDITION_1_1yes[,fieldid]*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        v_fieldid_age_c_X_CONDITION_2_1yes[,fieldid]*age_c*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes

)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_1_1yes[i], CONDITION_2_1yes[i], fieldid[i]))
pred5b_prime <- apply(pred.raw , 2 , mean)
pred.PI5b_prime <- apply( pred.raw , 2 , PI)











################# ESTIMATES FOR WÍCHI
fieldid <- rep(6, length)
age_c=age.seq6a
age_2c=age_c^2	
CONDITION_1_1yes = rep(1,length)
CONDITION_2_1yes = rep(0,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_1_1yes, CONDITION_2_1yes, fieldid) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_1_1yes*CONDITION_1_1yes +
        b_CONDITION_2_1yes*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        b_age_c_X_CONDITION_1_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        b_age_c_X_CONDITION_2_1yes*age_c*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes +
        v_fieldid_Intercept[,fieldid] +
        v_fieldid_CONDITION_altruistic_1yes[,fieldid]*CONDITION_altruistic_1yes +
        v_fieldid_age_c[,fieldid]*age_c +
        v_fieldid_CONDITION_1_1yes[,fieldid]*CONDITION_1_1yes +
        v_fieldid_CONDITION_2_1yes[,fieldid]*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c[,fieldid]*CONDITION_altruistic_1yes*age_c +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        v_fieldid_age_c_X_CONDITION_1_1yes[,fieldid]*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        v_fieldid_age_c_X_CONDITION_2_1yes[,fieldid]*age_c*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes

)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_1_1yes[i], CONDITION_2_1yes[i], fieldid[i]))
pred6a_prime <- apply(pred.raw , 2 , mean)
pred.PI6a_prime <- apply( pred.raw , 2 , PI)



CONDITION_1_1yes = rep(0,length)
CONDITION_2_1yes = rep(1,length)
p.link <- function( age_c, CONDITION_altruistic_1yes, CONDITION_1_1yes, CONDITION_2_1yes, fieldid) {
    logodds <- with( post , 
        b_CONDITION_altruistic_1yes*CONDITION_altruistic_1yes +
        b_age_c*age_c +
        b_CONDITION_1_1yes*CONDITION_1_1yes +
        b_CONDITION_2_1yes*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c*CONDITION_altruistic_1yes*age_c +
        b_CONDITION_altruistic_1yes_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        b_age_c_X_CONDITION_1_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        b_CONDITION_altruistic_1yes_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        b_age_c_X_CONDITION_2_1yes*age_c*CONDITION_2_1yes +
        b_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes +
        v_fieldid_Intercept[,fieldid] +
        v_fieldid_CONDITION_altruistic_1yes[,fieldid]*CONDITION_altruistic_1yes +
        v_fieldid_age_c[,fieldid]*age_c +
        v_fieldid_CONDITION_1_1yes[,fieldid]*CONDITION_1_1yes +
        v_fieldid_CONDITION_2_1yes[,fieldid]*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c[,fieldid]*CONDITION_altruistic_1yes*age_c +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_1_1yes +
        v_fieldid_age_c_X_CONDITION_1_1yes[,fieldid]*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_1_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_1_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*CONDITION_2_1yes +
        v_fieldid_age_c_X_CONDITION_2_1yes[,fieldid]*age_c*CONDITION_2_1yes +
        v_fieldid_CONDITION_altruistic_1yes_X_age_c_X_CONDITION_2_1yes[,fieldid]*CONDITION_altruistic_1yes*age_c*CONDITION_2_1yes

)
    return( (logodds) )}
pred.raw <- sapply( 1:length , function(i) p.link(age_c[i], CONDITION_altruistic_1yes[i], CONDITION_1_1yes[i], CONDITION_2_1yes[i], fieldid[i]))
pred6b_prime <- apply(pred.raw , 2 , mean)
pred.PI6b_prime <- apply( pred.raw , 2 , PI)








################# PLOTTING MODEL ESTIMATES




cexset.title = 1.75
cexset = 1.5
cexlegend = 1.3
x=0
y=.95
line=2.7


par(mfrow=c(2, 3))


################# PLOTTING BERLIN
plot( dataset$age_c , type="n" , xlab="Age in Years" , ylab="Effect Size of interaction" , axes=FALSE, ylim=c(-2.5,4.5), xlim=c(min(dataset$age_c),max(dataset$age_c)+.2), cex.lab=cexset )
legend(x="topleft", c("Punish-Selfish X Third Party Behavior", "Punish-Prosocial X Third Party Behavior"), bty="n", lwd = 2, lty=c(1,3), cex=cexlegend, col=col0 , text.col=col0 )
title(main="( A ) Berlin", cex.main=cexset.title, sub="", cex.sub=cexset)
axis(1, at=(seq(4,16,by=(2))-mean(dataset$AGE_in_years))/sd(dataset$AGE_in_years), lab=seq(4,16,by=(2)), cex.axis=cexset)    
axis(1, at=(seq(4,16,by=(1))-mean(dataset$AGE_in_years))/sd(dataset$AGE_in_years), lab=FALSE, cex.axis=cexset)    
axis(2, at=seq(-2,4,by=(1)), lab=seq(-2,4,by=(1)), cex.axis=cexset)   
lines( age.seq1a , pred1a_prime, lty=1, lwd=2, col=col1)
shade( pred.PI1a_prime , age.seq1a, col=shade1)
lines( age.seq1b , pred1b_prime, lty=3, lwd=2, col=col1)
shade( pred.PI1b_prime , age.seq1b, col=shade1)
abline(a=0, b=0)


################# PLOTTING LA PLATA
plot( dataset$age_c , type="n" , xlab="Age in Years" , ylab="Effect Size of interaction" , axes=FALSE, ylim=c(-2.5,4.5), xlim=c(min(dataset$age_c),max(dataset$age_c)+.2), cex.lab=cexset )
title(main="( B ) La Plata", cex.main=cexset.title, sub="", cex.sub=cexset)
axis(1, at=(seq(4,16,by=(2))-mean(dataset$AGE_in_years))/sd(dataset$AGE_in_years), lab=seq(4,16,by=(2)), cex.axis=cexset)    
axis(1, at=(seq(4,16,by=(1))-mean(dataset$AGE_in_years))/sd(dataset$AGE_in_years), lab=FALSE, cex.axis=cexset)    
axis(2, at=seq(-2,4,by=(1)), lab=seq(-2,4,by=(1)), cex.axis=cexset)   
lines( age.seq2a , pred2a_prime, lty=1, lwd=2, col=col2)
shade( pred.PI2a_prime , age.seq2a, col=shade2)
lines( age.seq2b , pred2b_prime, lty=3, lwd=2, col=col2)
shade( pred.PI2b_prime , age.seq2b, col=shade2)
abline(a=0, b=0)


################# PLOTTING PHOENIX
plot( dataset$age_c , type="n" , xlab="Age in Years" , ylab="Effect Size of interaction" , axes=FALSE, ylim=c(-2.5,4.5), xlim=c(min(dataset$age_c),max(dataset$age_c)+.2), cex.lab=cexset )
title(main="( C ) Phoenix", cex.main=cexset.title, sub="", cex.sub=cexset)
axis(1, at=(seq(4,16,by=(2))-mean(dataset$AGE_in_years))/sd(dataset$AGE_in_years), lab=seq(4,16,by=(2)), cex.axis=cexset)    
axis(1, at=(seq(4,16,by=(1))-mean(dataset$AGE_in_years))/sd(dataset$AGE_in_years), lab=FALSE, cex.axis=cexset)    
axis(2, at=seq(-2,4,by=(1)), lab=seq(-2,4,by=(1)), cex.axis=cexset)   
lines( age.seq3a , pred3a_prime, lty=1, lwd=2, col=col3)
shade( pred.PI3a_prime , age.seq3a, col=shade3)
lines( age.seq3b , pred3b_prime, lty=3, lwd=2, col=col3)
shade( pred.PI3b_prime , age.seq3b, col=shade3)
abline(a=0, b=0)


################# PLOTTING PUNE
plot( dataset$age_c , type="n" , xlab="Age in Years" , ylab="Effect Size of interaction" , axes=FALSE, ylim=c(-2.5,4.5), xlim=c(min(dataset$age_c),max(dataset$age_c)+.2), cex.lab=cexset )
title(main="( D ) Pune", cex.main=cexset.title, sub="", cex.sub=cexset)
axis(1, at=(seq(4,16,by=(2))-mean(dataset$AGE_in_years))/sd(dataset$AGE_in_years), lab=seq(4,16,by=(2)), cex.axis=cexset)    
axis(1, at=(seq(4,16,by=(1))-mean(dataset$AGE_in_years))/sd(dataset$AGE_in_years), lab=FALSE, cex.axis=cexset)    
axis(2, at=seq(-2,4,by=(1)), lab=seq(-2,4,by=(1)), cex.axis=cexset)   
lines( age.seq4a , pred4a_prime, lty=1, lwd=2, col=col4)
shade( pred.PI4a_prime , age.seq4a, col=shade4)
lines( age.seq4b , pred4b_prime, lty=3, lwd=2, col=col4)
shade( pred.PI4b_prime , age.seq4b, col=shade4)
abline(a=0, b=0)


################# PLOTTING SHUAR
plot( dataset$age_c , type="n" , xlab="Age in Years" , ylab="Effect Size of interaction" , axes=FALSE, ylim=c(-2.5,4.5), xlim=c(min(dataset$age_c),max(dataset$age_c)+.2), cex.lab=cexset )
title(main="( E ) Shuar", cex.main=cexset.title, sub="", cex.sub=cexset)
axis(1, at=(seq(4,16,by=(2))-mean(dataset$AGE_in_years))/sd(dataset$AGE_in_years), lab=seq(4,16,by=(2)), cex.axis=cexset)    
axis(1, at=(seq(4,16,by=(1))-mean(dataset$AGE_in_years))/sd(dataset$AGE_in_years), lab=FALSE, cex.axis=cexset)    
axis(2, at=seq(-2,4,by=(1)), lab=seq(-2,4,by=(1)), cex.axis=cexset)   
lines( age.seq5a , pred5a_prime, lty=1, lwd=2, col=col5)
shade( pred.PI5a_prime , age.seq5a, col=shade5)
lines( age.seq5b , pred5b_prime, lty=3, lwd=2, col=col5)
shade( pred.PI5b_prime , age.seq5b, col=shade5)
abline(a=0, b=0)


################# PLOTTING WICHÍ
plot( dataset$age_c , type="n" , xlab="Age in Years" , ylab="Effect Size of interaction" , axes=FALSE, ylim=c(-2.5,4.5), xlim=c(min(dataset$age_c),max(dataset$age_c)+.2), cex.lab=cexset )
title(main="( F ) Wichí", cex.main=cexset.title, sub="", cex.sub=cexset)
axis(1, at=(seq(4,16,by=(2))-mean(dataset$AGE_in_years))/sd(dataset$AGE_in_years), lab=seq(4,16,by=(2)), cex.axis=cexset)    
axis(1, at=(seq(4,16,by=(1))-mean(dataset$AGE_in_years))/sd(dataset$AGE_in_years), lab=FALSE, cex.axis=cexset)    
axis(2, at=seq(-2,4,by=(1)), lab=seq(-2,4,by=(1)), cex.axis=cexset)   
lines( age.seq6a , pred6a_prime, lty=1, lwd=2, col=col6)
shade( pred.PI6a_prime , age.seq6a, col=shade6)
lines( age.seq6b , pred6b_prime, lty=3, lwd=2, col=col6)
shade( pred.PI6b_prime , age.seq6b, col=shade6)
abline(a=0, b=0)



dev.off()
