QSG this week features a talk by Miranda Gao. The title of the the talk is “Applying Continuous Time Models to Experience Sampling Data with Unequal Time Intervals“. The abstract for the talk is given below.
Applying Continuous Time Models to Experience Sampling Data with Unequal Time Intervals by Miranda Gao.
The Experience Sampling Method (ESM) is useful to investigate a wide range of psychological processes, such as interpersonal relationships. People respond to questions about their current emotions or behaviors either prompted by a deliberately varied signal or contingent on the occurrence of a life event. Hence by design, ESM data are often unequally spaced within an individual and differ across individuals. Despite of its high ecological validity, ESM data, with the characteristic of unequal time intervals, can pose a challenge for discrete-time (DT) modeling. By ignoring the problem of unequal time intervals, parameter estimates obtained using DT models can be biased and uninterpretable; moreover, important information may be lost as the time elapsed between measurements may play a critical role in determining the intensity and dynamics of the psychological constructs. Thus, continuous-time (CT) models, by modeling time explicitly, accommodate the problems above. To illustrate how CT models contribute to our understanding of psychological dynamics, I fit both a DT model (i.e., multilevel VAR(1) model) and a hierarchical CT model to an ESM dataset in this project. When modeled in DT framework, individuals’ marital positivity in one conflict episode was not associated with their positivity in the next episode. Results obtained from CT framework, however, indicated that the null effect may be related to the rapid dissipation of marital positivity effect. That is, the effect of marital positivity tends to quickly decline to 0 within a time span of 6 hours. Implications and limitations of the project will be discussed.
QSG meets on Thursdays from 3:30-4:45pm in Corbett 378. All are welcome, and we hope to see you there.
For a complete list of speakers for Spring 2019, please visit this link.
The primary objective is to provide students the opportunity to develop their critical thinking skills, presentation abilities, and knowledge of the most recent developments in quantitative and statistical methods and techniques. The seminar format of this course is designed to stimulate and foster the intellectual environment of the program and department as well as to engage students at all levels. This is one of the required courses for non-quantitative students to get their minor in quantitative psychology. Quant minor requirements: https://psychology.nd.edu/graduate-programs/areas-of-study/quantitative/minor/