Determinants of linear judgment: A meta-analysis of lens model studies.

Abstract

The mathematical representation of E. Brunswik's (1952) lens model has been used extensively to study human judgment and provides a unique opportunity to conduct a meta-analysis of studies that covers roughly 5 decades. Specifically, the authors analyzed statistics of the "lens model equation" (L. R. Tucker, 1964) associated with 249 different task environments obtained from 86 articles. On average, fairly high levels of judgmental achievement were found, and people were seen to be capable of achieving similar levels of cognitive performance in noisy and predictable environments. Further, the effects of task characteristics that influence judgment (numbers and types of cues, inter-cue redundancy, function forms and cue weights in the ecology, laboratory versus field studies, and experience with the task) were identified and estimated. A detailed analysis of learning studies revealed that the most effective form of feedback was information about the task. The authors also analyzed empirically under what conditions the application of bootstrapping--or replacing judges by their linear models--is advantageous. Finally, the authors note shortcomings of the kinds of studies conducted to date, limitations in the lens model methodology, and possibilities for future research.

Personality, Resilience, Self-Regulation and Cognitive Ability Relevant to Teacher Selection

“…Previous research indicates that people are capable of making highly accurate judgments in many contexts (e.g. Karelaia & Hogarth, 2008;Kaufmann & Athanasou, 2009).…”

“…Social Judgment Theory uses Brunswick's Lens model to help understand the process people use in making a decision (Karelaia & Hogarth, 2008). Judgments are understood to be the result of integrating multiple cues that are probabilistically related to criteria.…”

Examination of gaze behaviors under in situ and video simulation task constraints reveals differences in information pickup for perception and action

“…There is a concern that psychology has largely "neglected the environment" (Dunwoody, 2006, p. 139) in preference for simplified research designs that emphasize experimental control at the risk of jeopardizing generalizability of conclusions (Araújo, Davids, & Passos, 2007;Dhami et al, 2004). Data from recent meta-analyses have revealed differences between laboratory studies and natural experimental settings for several measures of behavior, including perceptual expertise (Mann, Williams, Ward, & Janelle, 2007) and human judgment heuristics (Hogarth & Kareláia, 2007;Kareláia & Hogarth, 2008). Such observations highlight the need to adequately sample environmental constraints in experimental designs to understand functional human behavior.…”

“…The design of appropriate empirical task constraints is a major issue in experimental psychology (e.g., Brunswik, 1956;Dhami, Hertwig, & Hoffrage, 2004;Gibson, 1979;Hammond & Stewart, 2001;Kareláia & Hogarth, 2008). There is a concern that psychology has largely "neglected the environment" (Dunwoody, 2006, p. 139) in preference for simplified research designs that emphasize experimental control at the risk of jeopardizing generalizability of conclusions (Araújo, Davids, & Passos, 2007;Dhami et al, 2004).…”

A cognitive prosthesis for complex decision-making

“…Second, our measure of structural knowledge assumes linear relationships between the different situation variables (to estimate the overall direction and strength of relationships) and may consequently underestimate participants' knowledge if the latter is nonlinear. Still, we argue that our measure should be sensitive enough to detect differences in understanding, since linear estimation of non-linear relations has been shown to account for a significant proportion of variance in most cases (Karelaia and Hogarth, 2008). Third, the time allocated for creating a good internal representation of the structure of the system may have been too short.…”