Affect and Personality: Ramifications of Modeling (Non-)Directionality in Dynamic Network Models.
Affect and Personality: Ramifications of Modeling (Non-)Directionality in Dynamic Network Models.
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DOI:
10.1027/1015-5759/a000612
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发表时间:
2020
期刊:
影响因子:
--
通讯作者:
Molenaar PCM
中科院分区:
文献类型:
--
作者:
Park JJ;Chow SM;Fisher ZF;Molenaar PCM
The use of dynamic network models has grown in recent years. These models allow researchers to capture both lagged and contemporaneous effects in longitudinal data typically as variations, reformulations, or extensions of the standard vector autoregressive (VAR) models. To date, many of these dynamic networks have not been explicitly compared to one another. We compare three popular dynamic network approaches–GIMME, uSEM, and LASSO gVAR–in terms of their differences in modeling assumptions, estimation procedures, statistical properties based on a Monte Carlo simulation, and implications for affect and personality researchers. We found that all three approaches dynamic networks provided yielded group-level empirical results in partial support of affect and personality theories. However, individual-level results revealed a great deal of heterogeneity across approaches and participants. Reasons for discrepancies are discussed alongside these approaches’ respective strengths and limitations.
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DOI:
10.1348/000711010x497262
发表时间:
2011-02
期刊:
The British journal of mathematical and statistical psychology
影响因子:
--
作者:
Chow SM;Tang N;Yuan Y;Song X;Zhu H
通讯作者:
Zhu H
影响因子:
5
作者:
COHEN, S;KAMARCK, T;MERMELSTEIN, R
通讯作者:
MERMELSTEIN, R
影响因子:
3
作者:
Chow, Sy-Miin;Zhang, Guangjian
通讯作者:
Zhang, Guangjian
影响因子:
4.8
作者:
Epskamp, Sacha;van Borkulo, Claudia D.;Cramer, Angelique O. J.
通讯作者:
Cramer, Angelique O. J.
影响因子:
3.8
作者:
Epskamp, Sacha;Waldorp, Lourens J.;Borsboom, Denny
通讯作者:
Borsboom, Denny