ss.power.lrd {MBESS} | R Documentation |
Returns power given the sample size, or sample size given the desired power, for a longitudinal randomized design.
ss.power.lrd(beta, tau, level.1.variance, frequency, duration, desired.power = NULL, N = NULL, alpha.level = 0.05, standardized = TRUE, directional = FALSE)
beta |
the level two regression coefficeint for the group by time interaction; where "X" is coded -.5 and .5 for the two groups. |
tau |
the true variance of the individuals' slopes |
level.1.variance |
level one variance |
frequency |
frequency of measruemetns per unit of time duration of the study in the particular units (e.g., age, hours, grade level, years, etc.) |
duration |
time in some number of units (e.g., years) |
desired.power |
desired power |
N |
sample size |
alpha.level |
Type I error rate |
standardized |
the standardized slope is the unstandardized slope divided by the square root of tau, the variance of the unique effects for beta. |
directional |
should a one (TRUE ) or two (FALSE ) tailed test be performed. |
Ken Kelley (University of Notre Dame; KKelley@ND.Edu)
Raudenbush, S. W., & X-F., Liu. (2001). Effects of study duration, frequency of observation, and sample size on power in studies of group differences in polynomial change. Psychological Methods, 6, 387–401.
# Example from Raudenbush and Liu (2001) # ss.power.lrd(beta=-.4, tau=.003, level.1.variance=.0262, frequency=2, duration=2, desired.power=.80, alpha.level=.05, standardized=TRUE, directional=FALSE) # ss.power.lrd(beta=-.4, tau=.003, level.1.variance=.0262, frequency=2, duration=2, N=238, alpha.level=.05, standardized=TRUE, directional=FALSE) # The standardized effect size is obtained as beta/sqrt(tau): -.4/sqrt(.003) = -.0219. # ss.power.lrd(beta=-.0219, tau=.003, level.1.variance=.0262, frequency=2, duration=2, desired.power=.80, alpha.level=.05, standardized=FALSE, directional=FALSE) # ss.power.lrd(beta=-.0219, tau=.003, level.1.variance=.0262, frequency=2, duration=2, N=238, alpha.level=.05, standardized=FALSE, directional=FALSE)