Ginette Lafit, Jordan Revol, Mihai A. Constantin, & Eva Ceulemans
In recent years the popularity of procedures to collect intensive longitudinal
data such as the Experience Sampling Method has increased immensely. The data
collected using such designs allow researchers to study the dynamics of
psychological processes, and how these dynamics differ across individuals. A
fundamental question when designing a study is how to determine the sample size,
which is closely related to the replicability and generalizability of empirical
findings. Even though multiple statistical guidelines are available for sample
size planning, it still remains a demanding enterprise in complex designs. The
goal of this workshop is to address this crucial question by presenting
methodological advances for sample size planning for intensive longitudinal
designs. First, we provide an overview of methods for sample size planning with
special emphasis on a priori power analysis. Second, we focus on how to conduct
power analysis in the
The workshop provides a road map on how to determine the sample size in intensive longitudinal designs. Upon course completion, participants will:
- be familiar with methods for conducting power analysis for
$\text{AR}(1)$ and$\text{VAR}(1)$ models in$N = 1$ and multilevel intensive longitudinal designs - understand the key differences between simulation-based and analytical power analysis approaches
- be able to leverage existing tools for conducting power analysis for
$\text{AR}(1)$ and$\text{VAR}(1)$ for intensive longitudinal designs - be familiar with new methods for conducting sample size analysis based on criteria different than statistical power (e.g., predictive accuracy or sensitivity)
Participants should have some basic knowledge of R
and some experience with
RStudio
. For the hands-on parts of the workshop, you need to install R
version 4.1.2
or higher, RStudio
, and several R
packages as indicated on
the page corresponding to each exercise.
Some exercises in this workshop also involve using Shiny
applications to run
power analysis. You can find additional instructions on how to download and run
the Shiny
applications below:
- for Predictive Accuracy Analysis and power analysis for the $\text{VAR}(1)$
- for power analysis for multilevel models using the simulation-based approach
- for power analysis for multilevel models using the analytic approach
You can find detailed instructions and examples for conducting sample size
analysis using the powerly
package at powerly.dev.
Topic | Duration | Slides | Tutorial |
---|---|---|---|
Introduction to sample size planning in intensive longitudinal research | 45m | [slides]{.badge .rounded-pill .bg-primary} | - |
Sample size planning for |
60m | [slides]{.badge .rounded-pill .bg-primary} | [tutorial 1]{.badge .rounded-pill .bg-primary} [tutorial 2]{.badge .rounded-pill .bg-primary} |
Sample size planning for multilevel models applied to intensive longitudinal designs | 50m | [slides]{.badge .rounded-pill .bg-primary} | [tutorial 1]{.badge .rounded-pill .bg-primary} [tutorial 2]{.badge .rounded-pill .bg-primary} [tutorial 3]{.badge .rounded-pill .bg-primary} |
Advanced methods for sample size analysis | 40m | [slides]{.badge .rounded-pill .bg-primary} | [tutorial]{.badge .rounded-pill .bg-primary} |
Conference | Location | Date | Link |
---|---|---|---|
SAA 2023 | Amsterdam, The Netherlands | June 8th, 2023 | link |
- Lafit, G., Revol, J., Constantin M. A., & Ceulemans, E. (2023). Workshop on Sample Size Planning for Intensive Longitudinal Studies. https://doi.org/10.5281/zenodo.8015940