This course will take place over two days (10/29/24 and 10/31/24) and will be offered via Zoom. Attendance is required as the course will not be recorded.
Nesting can arise from hierarchical data structures (e.g., siblings nested within family; patients nested within therapist), longitudinal data structures (repeated measures nested within individual), or both (repeated measures nested within patient and patient nested within therapist).
It is well known that the analysis of nested data structures using traditional general linear models (e.g., ANOVA or regression) is flawed, oftentimes substantially so: Tests of significance are likely biased and within- and between-group effects are confounded with one another. All of these limitations can be addressed within the multilevel model.
This workshop provides an introduction to the application of multilevel models with nested data, including software implementation in SAS, SPSS and Stata.
The goal of this two-day series is to provide researchers with the knowledge, tools, and resources to aid in the development of a scientific protocol for a clinical research study. Both sessions will begin at 9 a.m. and a question-and-answer session will follow each presentation.
The first day of the series will provide an introduction and focus on the following key points:
- Who needs a clinical protocol and why it is important
- UNC Scientific Review Committee processes
- Types of clinical protocols, and content expectations for sections of the protocol
- Resources and tools available at UNC to support clinical protocol development
Target Audience: academic researchers, scientists, study coordinators, and students engaged in clinical research and/or clinical trials.
ACRP Contact Hours Update: The ACRP no longer approves 3rd party requests for CE credit. However, attendees are still welcome to self-report to ACRP for CE credit.
This 2-day course (10/30 & 10/31) will be offered ONLINE. It will not be recorded as there are in-class activities.
With increased interest in person-centered interventions and treatments has come increased interest in understanding human processes as they unfold within individuals. Additionally, technological advances have made the collection of person-specific data easier and more cost-effective for researchers interested in studying human behavior within everyday contexts. This two-day course focuses on using two popular network models to explore research questions concerning within-person processes.
This course is intended for individuals with research questions that can be answered using multivariate time series data/intensive longitudinal data. Examples of such data include daily diary data; data collected via self-report through ecological momentary sampling (ESM); passive data from cell phones; and other psychophysiological data such as MRI data or heart rate data.
The two network modeling frameworks presented in this course are graphicalVAR (GVAR) and Group Iterative Multiple Model Estimation (GIMME). Both models can be used to explore processes as they unfold within individuals to obtain individual person-specific network models (idiographic analysis) or group/population level network models (nomothetic analysis). Differences between the modeling frameworks will be presented. Challenges and considerations for choosing between methods will be discussed.