Nowadays, researchers can easily collect dozens and dozens of measurements of a single individual by using smartphones and other electronic devices. For these kinds of studies, participants are requested to fill in short questionnaires multiple times a day for a couple of weeks or even for months, in which they report how they feel, where they are, with whom they are, and so on. The purpose of these studies is to understand how the psychological variables of interest unravel over time given the individual experiences of each subject and the specific situations where the measurements occurred. In other words, the goal is to understand the psychological dynamics of each individual. The resulting data from these studies is known as intensive longitudinal data or time series data. However, analyzing this kind of data can be challenging as sophisticated statistical methods which are still in development are required. The studies in this dissertation discuss and further develop statistical methods to analyze intensive longitudinal data in psychology based on one fundamental question: What are we measuring? With this in mind, we focused on two topics: How to distinguish between “traits” and “states”, and how to account for measurement error when studying intensive longitudinal data.
|Qualification||Doctor of Philosophy|
|Place of Publication||[Groningen]|
|Publication status||Published - 2022|