Simulation Model Building. A Statistical Approach to Modelling in the Social Sciences with the Simulation Method

1974 ◽  
Vol 76 (3) ◽  
pp. 380
Author(s):  
Werner Meissner ◽  
Urban Norlén ◽  
Urban Norlen
Keyword(s):  
Social Sciences ◽  
Simulation Model ◽  
Statistical Approach ◽  
Model Building ◽  
Simulation Method ◽  
The Social

Social Ontology and Model-Building: A Response to Epstein

2021 ◽  
Vol 51 (2) ◽  
pp. 176-192
Author(s):  
Nadia Ruiz
Keyword(s):  
Social Sciences ◽  
Social Science ◽  
Model Building ◽  
Social Ontology ◽  
Model Construction ◽  
Ontological Commitments ◽  
Starting Point ◽  
The Social

Brian Epstein has recently argued that a thoroughly microfoundationalist approach towards economics is unconvincing for metaphysical reasons. Generally, Epstein argues that for an improvement in the methodology of social science we must adopt social ontology as the foundation of social sciences; that is, the standing microfoundationalist debate could be solved by fixing economics’ ontology. However, as I show in this paper, fixing the social ontology prior to the process of model construction is optional instead of necessary and that metaphysical-ontological commitments are often the outcome of model construction, not its starting point. By focusing on the practice of modeling in economics the paper provides a useful inroad into the debate about the role of metaphysics in the natural and social sciences more generally.

Stochastic Actor-Oriented Models for the Co-Evolution of Networks and Behavior: An Introduction and Tutorial

2019 ◽  
Vol 23 (3) ◽  
pp. 511-534 ◽  
Author(s):  
Yuval Kalish
Keyword(s):  
Social Sciences ◽  
Model Building ◽  
Network Evolution ◽  
Network Ties ◽  
Network Change ◽  
Step Model ◽  
The Social ◽  
Research Questions ◽  
Organizational Scholarship ◽  
And Behavior

Stochastic actor-oriented (SAO) models are a family of models for network dynamics that enable researchers to test multiple, often competing explanations for network change and estimate the extent and relative power of various influences on network evolution. SAO models for the co-evolution of network ties and actor behavior, the most comprehensive category of SAO models, examine how networks and actor attributes—their behavior, performance, or attitudes—influence each other over time. While these models have been widely used in the social sciences, and particularly in educational settings, their use in organizational scholarship has been extremely limited. This paper provides a layperson introduction to SAO models for the co-evolution of networks and behavior and the types of research questions they can address. The models and their underpinnings are explained in nonmathematical terms, and theoretical explanations are supported by a concrete, detailed example that includes step-by-step model building and hypothesis testing, alongside an R script.

Model Building in the Social Sciences.

1970 ◽  
Vol 133 (3) ◽  
pp. 488
Author(s):  
G. R. Fisher ◽  
Roger Peltier
Keyword(s):  
Social Sciences ◽  
Model Building ◽  
The Social

Simulation in Social Sciences

2007 ◽  
pp. 90-100 ◽  
Author(s):  
R. Axelrod
Keyword(s):  
Social Sciences ◽  
Simulation Model ◽  
State Of The Art ◽  
The State ◽  
Social Scientists ◽  
Third Way ◽  
Simulation Research ◽  
The Social

Advancing the state of the art of simulation in the social sciences requires appreciating the unique value of simulation as a third way of doing science, in contrast to both induction and deduction. Simulation can be an effective tool for discovering surprising consequences of simple assumptions. This chapter offers advice for doing simulation research, focusing on the programming of a simulation model, analyzing the results, sharing the results, and replicating other people’s simulations. Finally, suggestions are offered for building a community of social scientists who do simulation.

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