Approved For Release 2000/08/08 : CIA-RDP96-00789R002200410001-2 Meta-analysis of Forced-Choice Precognition Experiments 16 (Kruskal-Wallis one-way ANOVA, chi-square = 11.78, 4 df,p = .019). This outcome is due to the substantially lower quality of studies appearing in the Journal of the Society for Psychical Research. Study Quality in relation to Year of Publication Precognition effect sizes have remained constant over a half-century of research, even though the methodological quality of the research has improved significantly during this period. The correlation between directional effect size and year of publication is -.050 (t246 = -0.79, p = 429). The result is nearly identical for the predicted ES (roa6 = -.059, Pp = 358). Study quality and year of publication are, however, positively and significantly correlated (r246 = .239, p = 7.2.x 10°). See Figure 4. Critics of parapsychology have long believed that evidence for parapsychological effects disappears as the methodological rigor increases, The precognition database does not support this belief. FIGURE 4: (a) Directional Effect Sizes in relation to Year of Publica- tion, (b) Study Quality in relation to Year of Publication Least Squares Fit with 95% Confidence Limits DIRECTIONAL EFFECT SIZE STUDY QUALITY » 1930 1940 1950 1960 1970 1980 1990 1930 1940 1960 1960 1870-1980) 1980 YEAR OF PUBLICATION YEAR OF PUBLICATION Psychophysical Research Laboratories Approved For Release 2000/08/08 : CIA-RDP96-00789R002200410001-2
jain eat io | i | E E cet a Approved For Release 2000/08/08 : CIA-RDP96-00789R002200410001-2 Meta-analysis of Forced-Cholce Precognition Experiments 17 “REAL-TIME” ALTERNATIVES TO PRECOGNITON Investigators have long been aware of the possibility that precognition effects could be modelled without assuming either time reversal or backward causality. For example, outcomes from studies with targets based on indeterminate random number generators (RNGs) could be due to a causal influence on the RNG—a psychokinetic (PK) effect —rather than information acquisition concerning its future state. In experiments with targets based on prepared tables of random numbers, the possibility exists that the experimenter or other randomizer may be the actual psi source, unconsciously using “real-time” ESP combined with PK to choose an entry point in the random number sequence that will significantly match the “subject’s” responses. While this latter possibility may seem farfetched, it cannot be logically eliminated if one accepts the existing evidence for contemporaneous ESP and PK, and it has been argued that it is less farfetched than the alternative of “true” precognition. Morris (1982) discusses models of experimental precognition based on “real-time” psi alternatives and methods for testing “true” precognition. In general terms these methods constrain the selection of the target sequence sO as to eliminate nonprecognitive psi intervention. In the most common procedure, attributed to Mangan (1955), dice are thrown to generate a set of numbers which are mathematically manipulated to obtain an entry point in the random number table. This procedure is sufficiently complex “as to be apparently beyond the capacities of the human brain, thus ruling out PK because the ’PKer’ would not know what to do even via ESP” (Morris, 1982, p. 329). Two features of precognition study target determination procedures were coded to assess “real-time” psi alternatives to precognition: e@ Method of determining random number table entry point, @ Use of Mangan’s method. Methods of eliminating “real-time” psi alternatives have not been employed in studies with random number generators and have only been Psychophysical Research Laboratories Approved For Release 2000/08/08 : CIA-RDP96-00789R002200410001-2
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200410001-2 Meta-analysis of Forced-Choice Precognition Experiments 18 used ina small number of studies involving randomization by hand shuffling. These analyses are therefore restricted to studies using random number tables (N = 137). Method of Determining RNT Entry Point The reports describe six different methods of obtaining entry points in random number tables. If the study outcomes were due to subjects’ precognitive functioning rather than to alternative psi modes on the part of the experimenter or the experimenter’s assistants, there should be no difference in mean effect size across the various methods used to determine the entry point. Indeed, our analysis indicates that the study effect sizes do not vary systematically as a function of method of determining the entry point (Kruskal-Wallis one-way ANOVA by Ranks: chi-square = 8.29, 5 df, p = .141). Use of Mangan’s Method We find no significant difference in effect size between studies using complex calculations of the type introduced by Mangan to fix the random number table entry point and those that do not use such calculations (¢ = 0.92, df = 77, p = .359, 2-tailed). Psychophysical Research Laboratories Approved For Release 2000/08/08 : CIA-RDP96-00789R002200410001-2
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200410001-2 Meta-analysis of Forced-Choice Precognition Experiments 19 MODERATING VARIABLES The stability of precognition study outcomes over a 50-year period is also bad news. It shows that investigators in this area have yet to develop sufficient understanding of the conditions underlying the occurrence (or detection) of these effects to reliably increase their magnitude. We have identified four variables that appear to covary systematically with magnitude of precognition performance: @ Selected versus unselected subjects e Individual versus group testing @ Feedback level e Time interval between subject response and target genera- tion We are interested only in factors associated with hitting; therefore, our analyses are based on the directional study outcomes only. The analyses use the raw study significance levels and effect sizes; this results in uniformly more conservative estimates of relationships with moderating variables than when the analyses are based on quality-weighted significance levels and effect sizes. . Selected versus Unselected Subjects Our meta-analysis identifies eight subject populations: e Unspecified subject populations e Mixtures of several different populations e Animals e Students e Children e@ “Volunteers” e Experimenter(s) @ Selected subjects Psychophysical Research Laboratories Approved For Release 2000/08/08 : CIA-RDP96-00789R002200410001-2
| | I iene, nici eran Pacey imineaat nnn | | | Approved For Release 2000/08/08 : CIA-RDP96-00789R002200410001-2 Meta-analysis of Forced-Choice Precognition Experiments 20 Effect size magnitude varies significantly across these eight subject populations (Kruskal-Wallis one-way ANOVA, chi-square = 15.71, 7 df, p = .028). Significance levels and effect sizes by subject population are displayed in Figures 5 and 6. FIGURE 5: Significance Level by Subject Population (95% Confidence Limits.) MEAN DIRECTIONAL Z-SCORE 9 ) -O.8 -1.0 -1.8 (28) 0) (107), (31) (HD (13)_— (BS) -2.0 wese SE AAEM TOO EA ee AL STE SUBJECT POPULATION FIGURE 6: Effect Size by Subject Population (95% Confidence Limits.) 0.180 o.126 6.100 0.078 &.080 0.028 2.000 -9.0268 0.080 MEAN DIRECTIONAL EFFECT SIZE -0.078 “0.100 resekS ygre' POH ALTOONA ONL NTH CAT ESTED SUBJECT POPULATION Psychophysical Research Laboratories Approved For Release 2000/08/08 : CIA-RDP96-00789R002200410001-2