The Challenge of Representative Design in Psychology and Economics

We propose a penalized likelihood approach in hidden Markov models (HMMs) to perform automated variable selection. To account for a potential large number of covariates, which also may be substantially correlated, we consider the elastic net penalty containing LASSO and ridge as special cases. By quadratically approximating the non-differentiable penalty, we ensure that the likelihood can be maximized numerically. The feasibility of our approach is assessed in simulation experiments. As a case study, we examine the ‘hot hand’ effect, whose existence is highly debated in different fields, such as psychology and economics. In the present work, we investigate a potential ‘hot shoe’ effect for the performance of penalty takers in (association) football, where the (latent) states of the HMM serve for the underlying form of a player.

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A Static Game Study between Food Enterprises Based on Value Perception Differences of Food Quality and Safety

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.791-793.2171 ◽

2013 ◽

Vol 791-793 ◽

pp. 2171-2174

Author(s):

Yuan Fen Yin ◽

Yun Deng ◽

Xiu Li Sang

Keyword(s):

Food Quality ◽

Game Model ◽

Quality And Safety ◽

Static Game ◽

Safety Issues ◽

Value Perception ◽

Safety Mechanism ◽

Psychology And Economics ◽

Food Quality And Safety ◽

Food Market

Behavior strategy of food enterprises exerts a direct influence on food quality and safety. Against the backdrop of value perception differences on food quality and safety between different food enterprises, this paper establishes a static game model and based on prospect theory, explores the reasons for food quality and safety issues in our food market from the perspectives of psychology and economics. Finally, it presents a more scientific food quality and safety mechanism and countermeasures.

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The Role of Ergonomics, Psychology, and Economics in Studying Efficiency of Human Performance

Work Activity Studies Within the Framework of Ergonomics, Psychology, and Economics ◽

10.1201/9781351125000-1 ◽

2018 ◽

pp. 3-38

Author(s):

Gregory Z. Bedny ◽

Inna S. Bedny

Keyword(s):

Human Performance ◽

Psychology And Economics

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Predicting the Replicability of Social Science Lab Experiments

10.31222/osf.io/zamry ◽

2019 ◽

Author(s):

Adam Altmejd ◽

Anna Dreber ◽

Eskil Forsell ◽

Teck Hua Ho ◽

Juergen Huber ◽

...

Keyword(s):

Effect Size ◽

Large Scale ◽

Relative Effect ◽

New Findings ◽

Psychology And Economics ◽

Out Of Sample ◽

Sample Test ◽

Successful Replication ◽

Basic Features ◽

Main Effects

We measure how accurately replication of experimental results can be predicted by a black-box statistical model. With data from four large- scale replication projects in experimental psychology and economics, and techniques from machine learning, we train a predictive model and study which variables drive predictable replication.The model predicts binary replication with a cross validated accuracy rate of 70% (AUC of 0.79) and relative effect size with a Spearman ρ of 0.38. The accuracy level is similar to the market-aggregated beliefs of peer scientists (Camerer et al., 2016; Dreber et al., 2015). The predictive power is validated in a pre-registered out of sample test of the outcome of Camerer et al. (2018b), where 71% (AUC of 0.73) of replications are predicted correctly and effect size correlations amount to ρ = 0.25.Basic features such as the sample and effect sizes in original papers, and whether reported effects are single-variable main effects or two- variable interactions, are predictive of successful replication. The models presented in this paper are simple tools to produce cheap, prognostic replicability metrics. These models could be useful in institutionalizing the process of evaluation of new findings and guiding resources to those direct replications that are likely to be most informative.

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Regret in Decision Making

Current Directions in Psychological Science ◽

10.1111/1467-8721.00203 ◽

2002 ◽

Vol 11 (6) ◽

pp. 212-216 ◽

Cited By ~ 278

Author(s):

Terry Connolly ◽

Marcel Zeelenberg

Keyword(s):

Decision Making ◽

Comparative Evaluation ◽

The Other ◽

Research Issues ◽

New Approach ◽

Self Blame ◽

Psychology And Economics ◽

Core Components ◽

Decision Research

Decision research has only recently started to take seriously the role of emotions in choices and decisions. Regret is the emotion that has received the most attention. In this article, we sample a number of the initial regret studies from psychology and economics, and trace some of the complexities and contradictions to which they led. We then sketch a new theory, decision justification theory (DJT), which synthesizes several apparently conflicting findings. DJT postulates two core components of decision–related regret, one associated with the (comparative) evaluation of the outcome, the other with the feeling of self–blame for having made a poor choice. We reinterpret several existing studies in DJT terms. We then report some new studies that directly tested (and support) DJT, and propose a number of research issues that follow from this new approach to regret.

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