I have the following issues.
I have a data frame with 3 columns. One is my Treatment column, with 5 different Treatments, repeated 3 times. The second column is my variable column, which has 7 different variables for each treatment. The 3rd column is my value column, which contains values for all the measured values.
I'm trying to run,as the title says, ANOVA + Post-Hocs (Tukey)'s on this data frame, with the goal of trying to compare for the effect of treatments PER variable. Furthermore, I'm also trying to assign letters on significantly different values of the measured variables from applying the treatments.
I'm trying to prompt this outcome in chatgpt, but the result keeps comparing treatments vs variables instead, which is not what I want... Can anyone help? Been bashing my head against this for the last 2 days.
Thanks in advance.
# Set the seed for reproducibility
set.seed(1)
# Define the number of treatments, variables, and repetitions
num_treatments <- 5
num_variables <- 7
num_repetitions <- 3
# Generate the Treatment column
treatments <- rep(LETTERS[1:num_treatments], each = num_variables * num_repetitions)
# Generate the Variable column
variables <- rep(paste0("Var", 1:num_variables), times = num_treatments * num_repetitions)
# Generate the Value column
values <- rnorm(num_treatments * num_variables * num_repetitions)
# Create the data frame
data <- data.frame(Treatment = treatments, Variable = variables, Value = values)`
# Set the seed for reproducibility
set.seed(1)
# Define the number of treatments, variables, and repetitions
num_treatments <- 5
num_variables <- 7
num_repetitions <- 3
# Generate the Treatment column
treatments <- rep(LETTERS[1:num_treatments], each = num_variables * num_repetitions)
# Generate the Variable column
variables <- rep(paste0("Var", 1:num_variables), times = num_treatments * num_repetitions)
# Generate the Value column
values <- rnorm(num_treatments * num_variables * num_repetitions)
# Create the data frame
data <- data.frame(Treatment = treatments, Variable = variables, Value = values)
The following code generates a mock copy of my data.
For anova and post-hoc, I tried
model=aov(values~treatments+variables+treatments:variables,data=data)
tukey <- TukeyHSD(model)
But as mentioned, earlier, it doesn't give me what I want, which is for each variable, a comparison of treatment effects on the measured value. I therefore also can't proceed to trying multcompLetters4 on it. If I did it would probably look like
cld <- multcompLetters4(model, tukey)