get_power_table: Create a power table for a combination of parameter values

In powerlmm: Power Analysis for Longitudinal Multilevel Models

Description

Create a power table for a combination of parameter values

Usage

get_power_table(object, n2, ..., df = "between", alpha = 0.05,
  R = 1L, cores = 1L)

Arguments

object	An object created by study_parameters
n2	A vector of n2 values
...	Optional named arguments. Up to two extra arguments can be compared. When used together with the plot method, the first argument will be grouped by color and the second by facets.
df	Either "between" or "satterth" for Satterthwaite's DF approximation. Also accepts a numeric value which will be used as DF. See get_power
alpha	The alpha level, defaults to 0.05.
R	An integer indicating how many realizations to base power on. Useful when dropout or cluster sizes are sampled (i.e. are random variables).
cores	An integer indicating how many CPU cores to use.

Value

A data.frame with class plcp_power_table.

Examples

paras <- study_parameters(n1 = 11,
                          n2 = 10,
                          n3 = 6,
                          T_end = 10,
                          icc_pre_subject = 0.5,
                          icc_pre_cluster = 0,
                          var_ratio = 0.03,
                          icc_slope = 0.05,
                          cohend = -0.8)

# increase only n2
x <- get_power_table(paras, n2 = 10:15)
plot(x)

# Compare two parameters
x <- get_power_table(paras, n2 = 10:15, n3 = 6:8)
plot(x)

# Compare impact of three parameters
x <- get_power_table(paras, n2 = seq(3, 25, by = 3),
                            n3 = c(3,6,9),
                            icc_slope = c(0, 0.05, 0.1))
plot(x)

Example output

powerlmm documentation built on May 2, 2019, 3:10 a.m.