Hello
I would appreciate some advice about how to analyze my data.
These data come from an experiment during which the hearing of 18 ears was measured over time and according to different frequencies.
Each ear was measured at T1, T21, and T 28, and at each of its times, each ear was measured at frequencies 4000Hz, 8000Hz, 16000Hz, 25000Hz, and 32000Hz.
I especially want to know if there is a time effect. The frequency effect does not particularly interest me.
I was thinking of using a 2-factor anova for repeated data (with 2 factors within: time and frequency).
I work under R and I thought to use the lmer function with this code:
mod.lmer ← lmer(hearing ~ Point * Hz Frequency
+(1|id/Point) +(1|id/Hz Frequency
),
contrasts=list(Point=contr.sum, Frequency Hz
=contr.sum),
data=mydata)
id is the ear identification factor
I’m not sure about the coding of random effects (1|id/Point) +(1|id/Frequency Hz
), but they give me the same results as the aov.ez function in the afex package :
mod.ez ← aov_ez(id=“id”,
dv=“Threshold dB”,
data=mydata,
within = c(“Point”, “Frequency Hz”))
What do you think ?
Does this analysis seem correct to you? If not, what can you suggest me?
Thanks in advance for any help you can give me.
All the best