**Shiny app to perform power analysis to select the number of participants in intensive longitudinal studies.**
In recent years the popularity of procedures to collect intensive longitudinal data, such as the Experience Sampling Method, has immensely increased. The data collected using intensive longitudinal designs allow researchers to study the dynamics of psychological functioning, and how these dynamics differ across individuals. To this end, the data are often modeled with multilevel regression models. An important question that arises when designing intensive longitudinal studies is how to determine the number of participants needed to test specific hypotheses regarding the parameters of these models with sufficient power. We developed the Shiny app PowerAnalysisIL to compute power as a function of the number of participants in intensive longitudinal studies. The shiny app focuses on a set of research questions regarding intensive longitudinal data that can be estimated using specific multilevel regression models. These research questions include:
- Group differences in the mean level of the outcome of interest
- Effect of a level-2 continuous predictor on the mean level of the outcome of interest
- Effect of a level-1 continuous predictor on the outcome of
interest
- Group differences in the effect of a level-1 continuous
predictor on the outcome of interest
- Cross-level interaction effect between the continuous level-2 predictor and a continuous level-1 predictor
- Multilevel autoregressive models: mean autoregressive
effect
- Multilevel autoregressive models: group differences in the
mean autoregressive effect
- Multilevel autoregressive models: cross-level interaction effect between a continuous level-2 predictor and the lagged outcome of interest
The app was implemented using the R package shiny. It is stored in a git repository on GitHuB at https://github.com/ginettelafit/PowerAnalysisIL. Users can download the app and run locally on their computer by executing the following commands in R or Rstudio.
Here we also present:
1. The R code necessary to implement the PowerAnalysisIL shiny app and the syntax of the functions included in the R package to perform a power analysis to select the number of participants in intensive longitudinal studies.
2. R code to illustrate how to obtain the effect of interest and values for the model parameters based on previous studies or pilot data, which are used as input in the shiny app.
