per_treatment: Setup parameters that differ per treatment group
In powerlmm: Power Analysis for Longitudinal Multilevel Models

Description Usage Arguments Details Value See Also Examples

Helps specifying unequal cluster sizes with study_parameters, e.g. different number of clusters in the treatment and control arm, or different dropout patterns.

1	per_treatment(control, treatment)

`control`	Value used for control group
`treatment`	Value used for treatment group

The type of object passed to control and treatment will depend on the parameters in study_parameters that should have different values per treatment group.

An object of class "plcp_per_treatment"

unequal_clusters, study_parameters, dropout_weibull

n2 <- per_treatment(control = 10,
                    treatment = 20)
p <- study_parameters(n1 = 11,
                      n2 = n2,
                      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)