Graph data structures | Causal diagrams
Causal map
A causal map can be defined as a network consisting of links or arcs between nodes or factors, such that a link between C and E means, in some sense, that someone believes or claims C has or had some causal influence on E. This definition could cover diagrams representing causal connections between variables which are measured in a strictly quantitative way and would therefore also include closely related statistical models like Structural Equation Models and Directed Acyclic Graphs (DAGs). However the phrase “causal map” is usually reserved for qualitative or merely semi-quantitative maps. In this sense, causal maps can be seen as a type of concept map. Systems diagrams and Fuzzy Cognitive Maps also fall under this definition. Causal maps have been used since the 1970’s by researchers and practitioners in a range of disciplines from management science to ecology, employing a variety of methods. They are used for many purposes, for example: * As sketch diagrams to summarise causal links * As tools to understand how decisions are made * As tools to assist strategic planning * As tools to form and represent a consensus of expert views on “what causes what” in a subject area * As tools to investigate the differences in how different subjects view causal links in a subject area * As a way to encode the separate views of many different respondents on “what causes what” in a subject area * To represent “theories of change” and “program theory” in project management and evaluation Different kinds of causal maps can be distinguished particularly by the kind of information which can be encoded by the links and nodes. One important distinction is to what extent the links are intended to encode causation or (somebody’s) belief about causation. (Wikipedia).
