To install and load the library

```
install.packages("PowerUpR")
library(PowerUpR)
```

Statistical power, minimum detectable effect size (MDES), MDES
difference (MDESD), or minimum required sample size (MRSS) can be
requested by using the relevant function given design parameters. In
general, each function begins with an **output** name,
follows by a period, and ends with a **design** name in the
form `<output>.<design>()`

. There are three types
of output; `mdes`

for main effects (`mdes`

or
`mdesd`

for moderation effects), `power`

, and
`mrss`

. Each output can be requested for eighteen types of
designs to detect main treatment effect; `ira`

,
`ira_pn`

, `bira2`

, `bira2_pn`

,
`bira2f1`

, `bira2c1`

, `cra2`

,
`cra2_pn`

, `bira3`

, `bcra3r2`

,
`bcra3r2_pn`

, `bcra3f2`

, `cra3`

,
`bira4`

, `bcra4r2`

, `bcra4r3`

,
`bcra4f3`

, `cra4`

, and seven types of designs to
detect moderator effects; `mod211`

, `mod212`

,
`mod221`

, `mod222`

, `mod331`

,
`mod332`

, and `mod333`

. To detect mediator
effects, only `power`

can be requested for seven types of
designs; `med211`

, `med221`

, `med331`

,
`med321`

, `med311`

, `med_pn21`

,
`med_pn31`

, and `med_pn32`

.

For designs to detect main effects, first three letters stand for the
type of assignment; for individual random assignment `ira`

,
for blocked individual random assignment `bira`

, for cluster
random assignment `cra`

, and for blocked cluster random
assignment `bcra`

. First (or the only number) indicate total
number of levels. The single letter inbetween refers to whether the top
level is random or fixed. Partially nested designs are denoted with
`pn`

.

Naming conventions are slighlty different for designs to detect
moderator and mediator effects. Numbers following `mod`

keyword indicate total number of levels, the level at which
randomization takes place, and the level at which moderator resides
correspondingly. As for the mediator effects, numbers following
`med`

keyword indicate the level at which treatment, mediator
and outcome variables reside.

For example, the function `mdes.cra2()`

can be called to
calculate MDES for the main treatment effect in a two-level
cluster-randomized trial. Similiarly, the function
`mdesd.mod222()`

can be called to calculate MDESD for
moderator effect residing at level 2 in a two-level cluster-randomized
trial. Finally, the function `power.med221()`

can be called
to calculate statistical power for mediator residing at level 2 in a
two-level cluster-randomized trial.

Live app at:

https://powerupr.shinyapps.io/index/

**Acknowledgement**:

This work is supported by National Science Foundation through a collaborative research grant titiled “Power Analyses for Moderator and Mediator Effects in Cluster Randomized Trials” to Benjamin Kelcey (Award Number: 1437679), Jessaca Spybrook (Award Number:1437692), and Nianbo Dong (Award Number: 1437745).