Data from a longitudinal biology study. Is there a difference between groups over time? 3 independant factorial fixed effects (solution type with 2 levels, temperature with 3 levels, time with 19 levels) = 6 groups. There are 2 response variables (continuous variable: weight(mg)) and (percentage: (above last weight)). There will be a correlation between time readings as the same groups are measured over 19 time points.
This perhaps wants two models, one for the continuous response, one for percent.
Plot, model, assumptions, re-plot. Thank you!
ggplot(ab, aes(x = time, y = response, colour = type, group = type)) + geom_point() + geom_line() + facet_wrap(ab$temp) + scale_colour_manual(values = c(DS = "blue", MT = "green"), labels = c("Control", "Treatment")) + labs(colour='type') + xlab("") + ylab("") + scale_y_continuous(limits = c(0, 50)) + labs(title = "") + theme_bw() + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
Best code for the model & assumptions? Cheers in advance