R: lmmpower for power calculation in lmer model (interaction effects)
I'm trying to perform a power calculation for my longitudinal lmer model in R using longpower package function lmmpower. I have 2 questions. My data is measured at five timepoints ("time" = 4, 8, 16, 26, 52), and my my model is:
L4 <-lmer(outcome ~ time + X1 + X2 + drug + drug*time + X2*time + time^2 + (time|ID), data)
The goal of my model is to see if drug*time has a significant interactions (i.e. does drug affect the trajectory). I am confused about the "t"- or the time vector in lmmpower. Have I defined this correctly below??
lmmpower(L4, pct.change = 0.30, t = c(4, 8, 16, 26, 52), power = 0.80)
When I run these it tells me n=19.999.... So I would need 20 people in each group to detect a 30% change in the outcome, right? But I think I am doing this incorrectly, as I specifically want to know how I would detect a significant difference for the drug*time interaction. Is there a way I can specify this?
Thank you!
r
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I'm trying to perform a power calculation for my longitudinal lmer model in R using longpower package function lmmpower. I have 2 questions. My data is measured at five timepoints ("time" = 4, 8, 16, 26, 52), and my my model is:
L4 <-lmer(outcome ~ time + X1 + X2 + drug + drug*time + X2*time + time^2 + (time|ID), data)
The goal of my model is to see if drug*time has a significant interactions (i.e. does drug affect the trajectory). I am confused about the "t"- or the time vector in lmmpower. Have I defined this correctly below??
lmmpower(L4, pct.change = 0.30, t = c(4, 8, 16, 26, 52), power = 0.80)
When I run these it tells me n=19.999.... So I would need 20 people in each group to detect a 30% change in the outcome, right? But I think I am doing this incorrectly, as I specifically want to know how I would detect a significant difference for the drug*time interaction. Is there a way I can specify this?
Thank you!
r
add a comment |
I'm trying to perform a power calculation for my longitudinal lmer model in R using longpower package function lmmpower. I have 2 questions. My data is measured at five timepoints ("time" = 4, 8, 16, 26, 52), and my my model is:
L4 <-lmer(outcome ~ time + X1 + X2 + drug + drug*time + X2*time + time^2 + (time|ID), data)
The goal of my model is to see if drug*time has a significant interactions (i.e. does drug affect the trajectory). I am confused about the "t"- or the time vector in lmmpower. Have I defined this correctly below??
lmmpower(L4, pct.change = 0.30, t = c(4, 8, 16, 26, 52), power = 0.80)
When I run these it tells me n=19.999.... So I would need 20 people in each group to detect a 30% change in the outcome, right? But I think I am doing this incorrectly, as I specifically want to know how I would detect a significant difference for the drug*time interaction. Is there a way I can specify this?
Thank you!
r
I'm trying to perform a power calculation for my longitudinal lmer model in R using longpower package function lmmpower. I have 2 questions. My data is measured at five timepoints ("time" = 4, 8, 16, 26, 52), and my my model is:
L4 <-lmer(outcome ~ time + X1 + X2 + drug + drug*time + X2*time + time^2 + (time|ID), data)
The goal of my model is to see if drug*time has a significant interactions (i.e. does drug affect the trajectory). I am confused about the "t"- or the time vector in lmmpower. Have I defined this correctly below??
lmmpower(L4, pct.change = 0.30, t = c(4, 8, 16, 26, 52), power = 0.80)
When I run these it tells me n=19.999.... So I would need 20 people in each group to detect a 30% change in the outcome, right? But I think I am doing this incorrectly, as I specifically want to know how I would detect a significant difference for the drug*time interaction. Is there a way I can specify this?
Thank you!
r
r
asked Nov 14 '18 at 23:27
fwarnerfwarner
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