Modeling Affect Dynamics: State of the Art and Future Challenges

被引：113
作者：
Hamaker, E. L. [1 ]
Ceulemans, E. [2 ]
Grasman, R. P. P. P. [3 ]
Tuerlinckx, F. [2 ]
机构：
[1] Univ Utrecht, Fac Social & Behav Sci, Methodol & Stat, NL-3584 CH Utrecht, Netherlands
[2] Katholieke Univ Leuven, Res Grp Quantitat Psychol & Individual Difference, Leuven, Belgium
[3] Univ Amsterdam, Psychol Methods, NL-1012 WX Amsterdam, Netherlands
来源：
EMOTION REVIEW | 2015年 / 7卷 / 04期
关键词：
affective dynamics; intensive longitudinal data; within-person; DIFFERENTIAL-EQUATION MODEL; NEGATIVE AFFECT; BAYESIAN-ESTIMATION; COMPONENT ANALYSIS; SPECTRAL-ANALYSIS; TIME-SERIES; MULTIVARIATE; EXPERIENCE; SIMULATION; STRESS;
D O I：
10.1177/1754073915590619
中图分类号：
B84 [心理学];
学科分类号：
04 ; 0402 ;
摘要：
The current article aims to provide an up-to-date synopsis of available techniques to study affect dynamics using intensive longitudinal data (ILD). We do so by introducing the following eight dichotomies that help elucidate what kind of data one has, what process aspects are of interest, and what research questions are being considered: (1) single- versus multiple-person data; (2) univariate versus multivariate models; (3) stationary versus nonstationary models; (4) linear versus nonlinear models; (5) discrete time versus continuous time models; (6) discrete versus continuous variables; (7) time versus frequency domain; and (8) modeling the process versus computing descriptives. In addition, we discuss what we believe to be the most urging future challenges regarding the modeling of affect dynamics.
引用
收藏
页码：316 / 322
页数：7
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