Hi everyone, I’m trying to do a spaghetti plot and I know I’m doing all wrong, It must be.
What I need: 15 subjects, each with measurements over 5 different times (t1, ..., t5), and the variable that I need to represent in the spaguetti plot is given by: PCR = b0 + b1 * ti + epsilon B0, - baseline of each subject B1 - trajectory of each subject over time (so multiply by t) Epsilon - error associated with each subject Regression model with mixed effects. Thus, I generated b0, b1, epsilon and time created sequence. But I need to do spaguetti plot of the outcome and I can not understand how much I search the publications. Sorry for the stupidity, but I do not even know how to do it and I need it with the utmost urgency to finish a publication proposal :( Follows what I tried to do :( :( :( library(ggplot2) library(reshape) library(lattice) library(gtable) library(grid) set.seed(9027) n.longitudinal.observations = 5 # number of PCR measures (per subject) in the hospital period subjects = 15 # Number of simulations (1 per subject in the study) beta0_7_gerar = rnorm(subjects, mean = 1, sd = .5) beta0_7 = as.data.frame(matrix(beta0_7_gerar,nrow=subjects,ncol=1)) # beta 0 - input variable used to calculate PCR (the outcome) beta1_7_gerar = rnorm(subjects, mean = -1, sd = .5) beta1_7 = as.data.frame(matrix(beta1_7_gerar,nrow=subjects,ncol=1) ) # beta 1 - input variable used to calculate PCR (the outcome) tj_gerar = seq.int(1, n.longitudinal.observations, 1) epsilon_7_gerar = rnorm(5*subjects, mean = 0, sd = .1) epsilon_7 = as.data.frame(matrix(epsilon_7_gerar,nrow=subjects,ncol=1) ) # epsilon_7 - input variable used to calculate PCR (the outcome) - associated with each subject tj = as.data.frame(matrix(tj_gerar,nrow=subjects,ncol=1) ) # time point7 <- cbind(beta0_7, beta1_7, tj, epsilon_7) point7 point7 <- as.data.frame(point7) colnames(point7) = c("beta0_7","beta1_7","time", "epsilon_7") y_point7 <- point7$beta0_7 + point7$beta1_7*point7$time + point7 $epsilon_7 (the outcome of the study - PCR) y_point7 require(ggplot2) png('test.png') p = ggplot(y_point7, aes(time, y_point7)) + geom_line() print(p) dev.off() savehistory() OR: In the last part I also tried: ID = rep(1:3, each = 5) point7 <- cbind(ID,beta0_7, beta1_7, tj, epsilon_7) point7 point7 <- as.data.frame(point7) colnames(point7) = c("ID","beta0_7","beta1_7","time", "epsilon_7") y_point7 <- point7$beta0_7 + point7$beta1_7*point7$time + point7 $epsilon_7 y_point7 crp7 <- y_point7 head(point7, n = 15) ggplot(aes(x = tj_gerar, y = crp7), data = point7) + geom_line(aes(group = ID), color = "gray") + geom_smooth(aes(group = 1), method = "lm", size = 3, color = "red", se = FALSE) + theme_bw() But none of these worked :( I was looking to have something like: Being the outcome PCR and the year the times (1, 2, 3, 4, 5). Can someone help me please? Thanks, Best Rosa ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.