9.2 Causation
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Types of causal relationships Several types of causal models are developed as a result of observing causal relationships: common-cause relationships, common-effect relationships, causal chains and causal homeostasis.
The use of a controlled study is the most effective way of establishing causality between variables. In a controlled study, the sample or population is split in two, with both groups being comparable in almost every way. The two groups then receive different treatments, and the outcomes of each group are assessed.
Laura Lipton & Bruce Wellman bring us the theories of causation, which tend to fall into six categories. Curriculum, instruction, teachers, students, infrastructure and assessments.
What is a Causal Relationship? A causal relationship exists when one variable in a data set has a direct influence on another variable. Thus, one event triggers the occurrence of another event. A causal relationship is also referred to as cause and effect.
Plausibility (reasonable pathway to link outcome to exposure) Consistency (same results if repeat in different time, place person) Temporality (exposure precedes outcome) Strength (with or without a dose response relationship)
Causation means that one event causes another event to occur. Causation can only be determined from an appropriately designed experiment. In such experiments, similar groups receive different treatments, and the outcomes of each group are studied.
Causation is when one variable causes a change in another variable. For example, the job promotion in the first example caused the salary of the employee to increase. To determine whether one variable causes another to change, it's important to design and conduct an appropriate experiment.
Causal relationships between variables may consist of direct and indirect effects. Direct causal effects are effects that go directly from one variable to another. Indirect effects occur when the relationship between two variables is mediated by one or more variables.
