Month: March 2017

  • PIE: Ex Post Evaluation: Establishing Causality without Experimentation

    So far, we discussed evaluation based on ex ante Randomised Control Trials (RCT). In ex post experiments, we have an another opportunity for an evaluation. However, there are strong limitations: Treatment manipulation is no longer possible, observational data only (i.e. the outcome of social processes), and baseline may be missing To address these issues, the […]

  • PIE: Ex Ante Evaluations: Randomised Control Trials

    For a Randomised Control Trial (RCT) several elements are necessary. Evaluators need to be involved long before it ends – ideally from the conception. Randomisation must take place. The operationalisation and measurement must be defined. The data collection process and the data analysis must be performed rigorously. Randomisation and the data collection process is what […]

  • PIE: The Fundamental Problem of Causal Inference

    We evaluate policies for a multitude of reasons. On the one hand, we wish to increase our knowledge and learn about its underlying function to improve program design and effectiveness. On the other hand, considerations from economy, society, and politics are the reason behind the evaluation. This may include allocation decisions via cost-benefit analysis (economic), […]

  • ASC: Concepts and Arguments

    The evaluation of the correctness of arguments is the core of this blog post. We will focus on justifications as premises are to be evaluated with the scientific method. However, the quality of premises must be considered. Only true premises can guarantee the truth of the conclusion, so the reasons must be impeccable. Therefore, acceptable […]

  • SMABSC: Cognitive Agents

    Cognitive models are a representation of an agent control mechanism resembling the cognitive architecture of a mind.  It can be understood as a control system (e.g. a flow graph how to react) that takes sensory inputs and produces motor outputs (Piaget, 1985). More advanced models include adaptive memory (Anderson, 1983). Famous models include SOaR: State […]

  • SMABSC: Disease Propagation

    The SIR model was introduced as a mathematical model with differential equations (Kermack & McKendrick, 1927). The basic states are Susceptible, Infected, and Recovered. [latex]N_i = \frac{dS}{dt}+\frac{di}{dt}+\frac{dR}{dt}[/latex] In the SIR model, the fundamental trajectory of disease propagation could be captured, immunity was acquired after disease and the population is homogeneous. But the SIR model has […]

  • ISN: Communities and cliques

    Dyads are not yet interesting for network research. However, starting at triads interesting behaviour appear. In triads, balance and control appear. Triads appear more commonly in social networks than in random graphs. Clustering coeffcient The clustering coefficient measures the amount of transitivity in a network. When A is related to B, and B is in […]

  • PE: Redistribution

    The focus of today’s lecture will be on redistribution as discussed in Chapter 3(Mueller, 2003). Additionally, we will discuss papers quantitatively assessing the situation (De Haan & Sturm , 2017; Sturm & de Haan, 2015). A justification for the state can be redistribution. But redistribution itself can be argued for based on different reasons. In […]

  • ISN: Data Collection Strategies

    Data collection refers to the collection of an offline social network. The information about a particular community is collect. A group needs to be defined (boundaries), which may be easy (e.g. school class or company) or difficult (e.g. needle-sharing). Complete network data A group with clear boundaries, such as a formal group or organisation. All […]

  • ISN: Positions in Social Networks

    Positions in a network are important for different reasons such as well-being. In the following several concepts will be introduced to gauge positions in a social networks. Structural balance People prefer balanced relationship structures. According to Heider (Heider, 1946), imbalances cause psychological distress. To balance people create or drop ties. However, balance may not be […]