: CIA-RDP96-00789R002200610001-0 Approved For Release 2000/08/08 296 The Journal of Parapsychology TABLE 5 INDIVIDUAL VERSUS GROUP TESTING Individual Group N studies 97 105 Combined z 6.64 1.29 Studies with p < .05 30% 19% Mean ES O21 004 SDes .060 .066 t (200) = 1.89, p = .03 a unselected subjects: 27) = 1.51, p = 142, two-tailed. This result appears to reflect a general tendency toward increased rigor and more detailed reporting in studies with selected subjects. Individual Versus Group Testing Subjects were tested in groups, individually, or through the mail. Studies in which subjects were tested individually by an experimen- ter have a significantly larger mean ES than studies involving group testing (Table 5). The ¢ test of the difference is equivalent to a point-biserial cor- relation of .132, favoring individual testing. Of the studies with sub- jects tested individually, 30% are significant at the 5% level. The methodological quality of studies with subjects tested indi- vidually is significantly higher than that of studies involving group testing: (137) = 3.08, p = .003, two-tailed. This result is consistent with the conjecture that group experiments are frequently con- ducted as “targets of opportunity” and may often be carried out hastily in an afternoon without the preparation and planning that go into a study with individual subjects that may be conducted over a period of weeks or months. Thirty-five studies were conducted through the mail. In these studies, subjects completed the task at their leisure and mailed their responses to the investigator. These correspondence studies yield outcomes similar to those involving individual testing. The com- bined z score is 2.66, with a mean ES of 0.018 (SD = .082). ‘Ten correspondence studies (25.7%) are significant at the 5% level. Eleven studies are unclassifiable with regard to experimental set- ting. A Meta-Analysis of Forced-Choice Precognition Experiments 297 ‘TABLE 6 FEEDBACK RECEIVED BY SUBJECTS a Feedback of Results None Delayed Run score Trial-by-trial ee N studies 15 21 21 47 Combined z — 1.30 2.11 4,74 6.98 Studies with p < .05 0.0% 19.0% 33.3% 42.6% Mean £S — .001 009 .023 .035 SDes .028 .036 .048 .072 ph Feedback A significant positive relationship exists between the degree of feedback subjects receive about their performance and precognitive effect size (Table 6). Subject feedback information is available for 104 studies, These studies fall into four feedback categories: no feedback, delayed feedback (usually notification by mail), run-score feedback, and trial-by-trial feedback. We gave these categories numerical values between 0 and 3. Precognition effect size correlates .231 with feed- back level (102 df, p = .009). Of the 47 studies involving trial-by- trial feedback, 20 (42.6%) are significant at the 5% level. None of the studies without subject feedback are significant. Feedback level correlates positively though not significantly with research quality: r(102) = .173, p = .082, two-tailed. Inadequate randomization is the most plausible source of potential artifacts in studies with trial-by-trial feedback. We performed a separate analy- sis on the 47 studies in this group. Studies using formal methods of randomization do not differ significantly in mean ES from”those with informal randomization: i(15) = 0.67, p = .590, two-tailed. Similarly, studies reporting randomness control data do not differ significantly in ES from those not including randomness controls: (42) = 0.79, p = .436, two-tailed. Time Interval The interval between the subject’s response and target selection. ranges from less than one second to one year. Information about the time interval is available for 144 studies. This information, how- : CIA-RDP96-00789R002200610001-0 Approved For Release 2000/08/08
: CIA-RDP96-00789R002200610001-0 Approved For Release 2000/08/08 298 The Journal of Parapsychology Months - | - | 7 Weeks }- | | 17 5 Hours | = | 35 2 Minutes | —s | 19 ¥ Seconds Isec eee SES — O06 0.10 — 1.02 uy) (he Mean effect size Figure 5. Effect size by precognition interval, with 95% confidence limits. N = 144 studies. ever, is often imprecise. Our analysis of the relationship between precognitive ZS and time interval is therefore limited to seven broad interval categories: milliseconds, seconds, minutes, hours, days, weeks, and months. (Effect sizes by precognition interval are dis- played in Figure 5.) Although it is confounded with degree of feedback, there is a significant decline in precognition ES over increasing temporal dis- tance: r(142) = —.199, p = 017, two-tailed. ‘The largest effects oc- cur over the millisecond interval: N = 31 studies, combined z = 6.03, mean ES = 0.045, SD = .073. The smallest effects occur over periods ranging from a month to a year: N = 7, combined z = 0.53, mean £S = 0.001, SD = .049. Interestingly, the decline of precognition performance over in- creasing temporal distances results entirely from studies using; we- A Meta-Analysis of Forced-Choice Precognition Experiments 299 selected subjects: 7(122) = —.235, p = .009, two-tailed. Studies with selected subjects show a nonsignificant positive relauonship between ES and time interval: r(18) = .077, p = .745, two-tailed. Although the difference between these two correlations is not significant (2 = 1.24), this suggests that the origin of the decline over time may be motivational rather than the result of some intrinsic physical bound- ary condition. The relationship between precognition ES and feed- back also supports this conjecture. Nevertheless, any finding sug- gesting potential boundary conditions on the phenomenon should be vigorously pursued. Influence of Moderating Variables in Combination The above analyses examine the impact of each moderating var- iable in isolation. In this final set of analyses, we explore their joint influence on precognition performance. For this purpose, we iden- tify two subgroups of studies. One subgroup is characterized by the use of selected subjects tested individually with trial-by-trial feed- back. We refer to this as the Optimal group (N = 8 studies). The second group is characterized by the use of unselected subjects tested in groups with no feedback. We refer to this as the Suboptimal group (N = 9 studies). ‘The Optimal studies are contributed by four independent inves- ‘tigators and the Suboptimal studies are contributed by two of the same four investigators. All of the Optimal studies involve short pre- cognition time intervals (millisecond interval); the Suboptimal stud- ies involve longer intervals (intervals of weeks or months). All of the Optimal studies and 5 of the 9 Suboptimal studies use RNG meth- odology. The two groups do not differ significantly in average sam- ple size. The mean study quality for the Optimal group is signifi- cantly higher than that of the Suboptimal studies: Optimal mean = 6.63, SD = 0.92; Suboptimal mean = 3.44, SD = 0.53; 410) = 8.63, p = 3.3 x 107°, two-tailed. ‘The combined impact of the moderating variables appears to be quite strong (Table 7). Seven of the 8 Optimal studies (87.5%) are independently significant at the 5% level, whereas none of the Sub- optimal studies are statistically significant. All four investigators con- tributing studies to the Optimal group have significant outcomes.” “In the untrimmed sample of 309 studies, there are a total of 17 Optimal studies. The mean ES is 0.117 (SD = .154), and the combined z is 15.84. The percentage of independently significant studies is virtually the same as it is in the trimmed sample: 15 of the 17 studies (88.2%) are significant. : CIA-RDP96-00789R002200610001-0 Approved For Release 2000/08/08