Representational effects in causal judgment

Payton, Teresa (2006) Representational effects in causal judgment. (MSc(R) thesis), Kingston University, .


A fictitious virus-disease scenario was used to study representational effects in causal reasoning. In five studies, six different judgement conditions were created by crossing two levels of virus-disease covariation (0, .5) with three levels of disease base rate (.25, .5, .75). In the first study, the covariation information was presented as four propositions summarising the frequencies of the four patient types, namely patients or without the virus, who either did have or did not have the disease. In the second and third studies the same information was presented in a 2 x 2 table; in the second study the cell frequencies were presented as Arabic numerals, in the third study they were represented iconistically (the presence/absence of virus/disease was shown as schematic faces that varied in expression and colour). In the fourth study the covariation information was presented in terms of a branching tree with the two main branches representing the frequencies of patients with and without the disease from which sprouted smaller branches showing the frequency of those with and without the virus. In the final study the information was presented around a numberline, two boxes above the numberline divided the length of the numberline into two, showing the frequency of people with and without the disease; below the numberline shaded boxes showed the frequency of those with and without the virus. Causal judgements were poorest when the information was presented as propositions, reflected significantly improved covariation . discrimination when information was presented in 2 x 2 tables and as part of a numberline, but were most normative when the information was presented in the branching tree format. These results signal the presence of important representational effects in causal induction tasks, which if developed, could be useful as a cognitive tool to enhance a layperson's comprehension of probabilistic relationships.

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