Table 1. Studies included in the meta-analyses by decision domain and decision-maker expertise.
Study | Judges | Number of judgments | Number of cues | Judgment task | Criterion | Task results | |
---|---|---|---|---|---|---|---|
a) | Medical science, experts: | ||||||
1) | Nystedt & Magnusson [23] | 4 clinical psychologists | 38 | 3 | Judge patients based on patient | Rating on three | I: Δ1 = .11 |
protocols: | psychological tests (■) | II: Δ2 = .03 | |||||
I: intelligence | II: Δ3 = .12 | ||||||
II: ability to establish contact | (*, +, s) | ||||||
III: control of affect and impulses | |||||||
2) | Levi [24] | 9 nuclear medicine | 280 | 5 | Assess probability of significant | Coronary angiography | Δ4 = .07 |
physicians | (60 replications) | coronary artery disease based on patient | (*, s) | ||||
profiles | |||||||
3) | LaDuca, Engel, & Chovan [25] | 13 physicians | 30 | 5 | Judge the degree of severity | A single physician’s | Δ5 = .08 |
(congestive heart failure) based on | judgment (▲) | (*, s) | |||||
patient profiles | |||||||
4) | Smith, Gilhooly, & Walker [26] | 40 general practitioners | 20 | 8 | Decision to prescribe an antidepressant | Guideline expert (▲) | Δ6 = -.05 |
based on patient profile | (s) | ||||||
5a) | Einhorn [27] (This publication | 3 pathologists | III: 193 | 9 | Evaluate the severity of Hodgkin’s | Actual number of | III: Δ7 = -.01 |
contains two studies) | disease based on biopsy slides | months of survival | (s) | ||||
Second study | |||||||
6a) | Grebstein [28] | 10 clinical experts | 30 profiles | 10 | Judge Wechsler-Bellevue IQ scores | IQ test scores (■) | Δ8 = -.17 |
(varying in amounts of | from Rorschach psychograms | Δ9 = -.14 | |||||
clinical experience) | |||||||
5b | Einhorn [27] | 29 clinicians | I: 77 MMPI profiles | 11 | Judge the degree of neuroticism- | Actual diagnosis (■) | Δ10 = .02 |
First study (This publication | II: 181 MMPI profiles | psychoticism | Δ110 = -.05 | ||||
Contains two studies) | (*, +, s) | ||||||
7) | Todd (1955, see [29]), Note 3 | 10 clinical judges | 78 | 19 | Estimate patient IQ from the Rorschach | IQ test scores (■) | Δ12 = .05 |
test | |||||||
8) | Speroff, Connors, & Dawson | 123 physicians: | 440 | 32 | Judge intensive care unit patients’ | Patients’ actual | Δ13 = .05 |
[30] | 105 house staff, | hemodynamic status | hemodynamic status | (s) | |||
15 fellows, | (physicians’ estimation) | ||||||
3 attending physicians | |||||||
Novices: | |||||||
6b) | Grebstein [28] | 5 students | 30 | 10 | Judge Wechsler-Bellevue IQ scores | IQ test scores (■) | Δ14 = -.19 |
from Rorschach psychograms based on | |||||||
paper profiles | |||||||
b) | Business science, experts: | ||||||
9) | Ashton [31] | 13 executives, managers, | 42 | 5 | Predict advertising sales for Time | Actual advertising pages | Δ15 = .07 |
sales personnel | magazine based on case descriptions | sold | (*, +, s) | ||||
10) | Roose & Doherty [32] | 16 agency managers | 200 / 160 | 64 / 5 | Predict the success of life insurance | One-year criterion for | Δ16 = -.08 |
salesmen based on paper profiles | success | (*, +, s) | |||||
11) | Goldberg [33] | 43 bank loan officers | 60 | 5 | Predict bankruptcy experience based on | Actual bankruptcy | Δ17 = .03 |
large corporation profiles | experience | ||||||
12) | Kim, Chung, & Paradice [34] | 3 experienced loan | 119 | 7 | Judge whether a firm would be able to | Actual financial data | I: Δ18 = .09 |
officers | I: 60 big firms, | repay the loan requested based on | II: Δ19 = .02 | ||||
II: 59 small firms | financial profiles | (*, +, s) | |||||
13) | Mear & Firth [35] | 38 professional security | 30 | 10 | Predict security returns based on | Actual security returns | Δ20 = .03 |
analysts | financial profiles | (s) | |||||
14) | Ebert & Kruse [36] | 5 securities analysts | 35 | 22 | Estimate future returns of common | Actual returns | Δ21 = .06 |
stocks | |||||||
15) | Wright [37] | 47 students | 50 | 4 | Predict price changes for stocks from | Actual stock prices | Δ22 = .06 |
1970 until 1971 based on paper profiles | (*, +, s) | ||||||
of securities | |||||||
16) | Harvey & Harries [38] | 24 psychology students | 40 | Not | Forecast sales outcomes based on paper | Actual sales outcome | Δ23 = -.07 |
(1. experiment) | known | profiles | (s) | ||||
17) | Singh, 1990 [39] | 52 business students | 35 | Not | Estimate of the stock price of a | Actual stock prices | Δ24 = .02 |
known | company based on paper profiles | (s) | |||||
c) | Educational science, experts: | ||||||
18) | Dawes [40] | 1 admission committee | 111 | 4 | Admission decision for graduate school | Faculty ratings of l | Δ25 = .06 |
based on paper profiles | performance in graduate | ||||||
school (▲) | |||||||
19) | Cooksey, Freebody, & Davidson | 20 teachers | 118 | 5 | Judge I: Reading comprehension | I-II: End-of-year test | I: Δ26 = .04 |
[41] | And II: Word knowledge of | scores (■) | II: Δ27 = .04 | ||||
kindergarten children based on paper | (*, +, s) | ||||||
profiles | |||||||
Novices: | |||||||
20) | Wiggins & Kohen [42] | 98 psychology graduate | 110 | 10 | Forecast first-year-graduate grade point | Actual first-year- | Δ28 = .17 |
students | averages based on paper profiles | graduate grade point | (s) | ||||
averages | |||||||
21) | Wiggins, Gregory, & Diller, | 41 psychology students | 90 | 10 | Forecast first-year-graduate grade point | Actual first-year- | Δ29 = .06 |
see Dawes and Corrigan [43], | averages based on paper profiles | graduate grade point | |||||
repl. Wiggins and Kohen [42] | averages | ||||||
22) | Athanasou & Cooksey [44] | 18 technical and further | 120 | 20 | Judge whether students are interested in | Actual level of students’ | Δ30 = .07 |
education students | learning based on paper profile | interest | (*, +, s) | ||||
d) | Psychological science, experts: | ||||||
23) | Szucko & Kleinmuntz [45] | 6 experienced polygraph | 30 | 3–4 | Judge truthful / untruthful response | Actual theft | Δ31 = -.06 |
interpreters | based on polygraph protocols | (*, +, s) | |||||
24) | Cooper & Werner [46] | 18 | 33 | 17 | Forecast violent behavior during the | Actual violent behavior | Δ32 = .00 |
(9 psychologists, | first six months of incarceration based | during the first six | (s) | ||||
9 case managers) | on inmates’ data forms | months of imprisonment | |||||
25) | Werner, Rose, Murdach, & | 5 social workers | 40 | 19 | Predict imminent violence of | Actual violent acts | Δ33 = .03 |
Yesavage [47] | psychiatric inpatients in the first 7 days | in the first 7 days | (*, +, s) | ||||
following admission based on | following admission | ||||||
admission data | |||||||
26) | Werner, Rose, & Yesavage [48] | 30 | 40 | 19 | Predict male patients’ violent behavior | Actual violence during | Δ34 = .06 |
(15 psychologists, | during the first 7 days following | the first 7 days following | (s) | ||||
15 psychiatrists) | admission based on case material | admission | |||||
Novices: | |||||||
27) | Gorman, Clover, & Doherty [49] | 8 students | 75: | I, III: 12 | Predict students’ scores on an attitude | Actual data: | I: Δ35 = .73 |
I, III: 50 | II, IV: 6 | scale (I, II) and a psychology | I, II: Attitude scale | II: Δ36 = .67 | |||
II, IV: 25 | examination (III, IV) based on | III, IV: Examination scale | III: Δ37 = .01 | ||||
interviews (I, III) and paper profiles | (■) | IV: Δ38 = .29 | |||||
(II, IV) | (*, s) (.08), see | ||||||
Camerer [6] | |||||||
28) | Lehman [50] | 14 students | 40 | 19 | Assess imminent violence of male | Actual violent acts in the | Δ39 = -.01 |
patients in the first 7 days following | first 7 days following | (*, +, s) | |||||
admission based on case material | admission |
▲ = subjective criterion;
■ = test criterion;
(*) = idiographic approach (cumulating across individuals);
(*, +) = both research approaches are considered;
Δ = the success of bootstrapping models (see Eq 2); s = sub-sample of tasks for the second evaluation (psychometric corrected bootstrapping models).