Calculate power for two- and three-level multilevel longitudinal
studies with missing data. Both the third-level factor (e.g. therapists,
schools, or physicians), and the second-level factor (e.g. subjects),
can be assigned random slopes. Studies with partially nested designs,
unequal cluster sizes, unequal allocation to treatment arms, and different
dropout patterns per treatment are supported. For all designs power can be
calculated both analytically and via simulations. The analytical
calculations extends the method described in Galbraith et al. (2002)
|Author||Kristoffer Magnusson [aut, cre]|
|Date of publication||2018-03-20 19:08:03 UTC|
|Maintainer||Kristoffer Magnusson <[email protected]>|
|License||GPL (>= 3)|
|Package repository||View on CRAN|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.