Study 1's best-fitting model yields significant GPD and emotion effects on goals and performance¶

Claim · All claims
Evidence · 1 study · associational r? · q3
Currency · newest study 2022 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i? In Study 1's best-fitting model, the GPD and aggregate-emotion parameters for the goal and performance equations were estimated as significant (95% HDIs excluding zero), with discrete-emotion effects varying in sign. → The Dynamic Interplay Between Goal Setting 2022

Evidence¶

The Dynamic Interplay Between Goal Setting 2022¶

The Dynamic Interplay Between Goal Setting, Performance, and Emotions in Self-Regulated Learning: A Computational Modeling Approach — Supplementary Materials. (2022). https://gpemodel.shinyapps.io/gpe-model/

q3 · i? · associational · r?

Hierarchical Bayesian parameter estimates for Study 1's best-fitting model, reported in Supplementary Table S4 under the article's convention that a starred median is one whose "95% HDI does not include 0 and is therefore significant". The table marks the GPD-to-performance and aggregate-emotion-to-performance parameters as significant, with discrete-emotion estimates varying in sign.

"* denotes a median parameter estimate whose 95% HDI does not include 0 and is therefore significant."

Discussion¶

Related Claims¶

• Alternate models isolate the roles of goal success/failure, GPD effects, and emotion effects in the GPE framework — related
• Trait depression, anxiety, and negative emotionality correlate with baseline emotion parameters but not with temporal dynamics (Study 1) — related
• The GPE model's parameters are recoverable via Bayesian estimation in simulation — related