#MOTION ANALYSIS MODELS

data <- read.table('damselmotion.csv', header=TRUE, sep=',')

library(lme4)

library(emmeans)

data$trial <- as.factor(data$trial);

data$orientation <- as.factor(data$orientation);

data$angle <- as.factor(data$angle);

data$size <- as.factor(data$size);

data$fish=as.factor(data$fish);

fit1=lmer((st)~ angle +size *orientation +(1|fish/trial), data=d)

fit2=lmer((st)~ angle *size + orientation +(1|fish/trial), data=d)

fit3=lmer((st)~ angle *size *orientation +(1|fish/trial), data=d)

anova(fit1,fit3) # to test if interaction is significant

anova(fit2,fit3)

anova(fit3)#fit3 was best fit

hist(residuals(fit3),40) #check normality of residuals

plot(fit3) #check linearity of residuals

qqnorm(residuals(fit3)) #more checking of residual normality

qqline(residuals(fit3))

emmeans (fit3, specs = pairwise ~ angle * orientation*size, by= "angle",adjust = "bonf" )