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Distant Mental Influence of Hemolysis Rate
tl
ward hitting, a single-mean
t test may be calculated for the nine
t values,
comparing them with MCE =
0; such a test yields evidence for significant
hitting (X =
1.63, SD = 2.23,
t [8] = 2.01, p —
.035, one-tailed).
In the overall (ANOVA) analysis, no effect was found for the Source
variable: Scores for the “own” and “another’s” groups were virtually
identical. The Source x
Condition effect, which would have indicated a
dependence of the protect versus control effect upon the source of the
blood, was clearly nonsignificant. Therefore, we must conclude that blood
source was not an important variable in this investigation. However, an
interesting trend emerges when we examine the blood source for the nine
independently significant subjects. For this subgroup (for which there was
evidence for a psi effect), a comparison of the t scores of the five subjects
who influenced their own blood with those of the four subjects who in-
fluenced another person’s blood yields a trend of greater positive scoring
(i.e., psi hitting) for the “own blood” subjects (see Table 4). Because of
the small number of subjects involved in the comparison, this trend is not
significant
(
t
[7] =
1.73, p =
.12, two-tailed). The large magnitude of
the difference, however, suggests
that blood source would be an
inter-
esting variable to explore in future studies of this type.
An anonymous referee of this paper described the results of a post hoc
analysis that he or she performed on the “own” versus “other” scores;
that analysis pointed to a possible true scoring pattern for the two blood
source conditions. The referee reported that for die 14 subjects who
worked with their own blood cells, a 2 x 2 table can be constructed that
divides them by positive versus negative change score x
significant
versus nonsignificant change. Of the 7 with positive change, 5 were sig-
nificant; of the other 7, none were significant (p <
.02). The corre-
sponding table for the 18 subjects working with someone else’s blood cells
yields nonsignificant differences for these same classifications.
The raw data collected in this experiment were sent to researchers at
SRI International so that they might perform certain mathematical anal-
yses of the scores to determine which of two models of psi, the RA model
or the IDS model, would provide better predictions of the obtained re-
sults
for the 2-tube versus
8-tube conditions. Space
limitations do not
Table 4
Comparison of Own vs. Another’s
t Scores for Independently
Significant Subjects
Own
Another’s
2.52
-2.17
2.14
2.96
3.39
-2.79
3.04
3.08
2.53
X = 2.72
X = 0.27
SD = 0.44
SD = 2.76
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Journal of the American Society for Psychical Research
permit a detailed description of the rationale, nature, or specific results of
those analyses. However, the gist of their conclusion was that the extreme
heterogeneity of the data made
it impossible to make an adequate determi-
nation of which model provided a better fit of the obtained scores. They
argued that psychic functioning, whatever
its underlying mechanism,
is
highly individualized, making
it difficult to
test a specific theory using
data combined across subjects; in the present experiment, insufficient data
were collected for any one subject to allow tests of RA versus IDS predic-
tions within individuals. Additional details regarding the IDS/RA analyses
may be found in an SRI International technical report (Hubbard, Utts, &
Braud, 1987).
,
.
,
.
We conducted our own analyses of the tube number factor simply by
comparing the differences between the mean change scores for the control
and the protect periods for the 2-tube condition with the corresponding
differences for the 8-tube condition. Matched
t tests were used for these
comparisons. One
t test was calculated using the 'data from all 32 partic-
ipants. A second t test was calculated using the data from only the 9 par-
ticipants whose scoring rates had been independently significant. Neither
analysis indicated a significant difference between the two tube conditions
(X difference = 0.08, t [31] = 0.25, p =
.80, two-tailed, and X differ-
ence = 0.41, t [8] = 0.74, p =
.51, two-tailed , respectively) . According
to our understanding of the IDS model, psi scoring rate should be higher
for the 2-tube than for the 8-tube condition (i.e., scoring rate should de-
cline with “n length”). According to a direct psychokinesis or RA model,
psi scoring rate should not depend upon the number of tubes being mea-
sured during a participant’s “effort” period
(i.e., scoring rate should be
independent of “n length”). 5 Thus, the absence of a 2-tube versus 8-tube
scoring difference
is more consistent with a remote action than with an
IDS interpretation.
.
George Hansen (personal communication, May
28,
1988)
raised an
issue concerning the
statistical analysis of the present study. The issue
concerns the assumption of independence of measurements within a 15-
minute period. He mentioned that substantial
trial dependencies have
been observed in some of the biological target systems used by other in-
vestigators and wondered whether similar dependencies might be present
in
this hemolysis work.
If the individual
“trials”
(i.e., tube measure-
ments) are not independent, then the
t tests might not be appropriate. This
independence issue may be addressed as follows:
1 .
Trial dependence would be more problematical
in a situation
in
5 Some models of PK or RA could predict
a diminished
psi
effect, of the
level of the
individual
trial (or
at the
level of the individual tube ,
in the present study)
for long
as
opposed to short
41n lengths” due to a kind of “watering down” or “spreading thin
effect
of the increased number of targets
at the greater n length. The total psi effect for the entire
ensemble of larae n events, however, should be comparable to that for the entire ensemble of
small n events.
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Distant Mental Influence of Hemolysis Rate
which the very same target organism participated
in
all
trials of an ex-
tended measurement block— for example, placing a laboratory rat in a test
apparatus for 15 minutes and measuring
its activity 10 times (i.e., for 10
“trials”) during that long period. In the present hemolysis experiment, a
different tube of blood (with different target cells) was used for each of the
“trials” (i.e., tube measurements) within a 15-minute epoch. This is anal-
ogous to making
activity measurements
in 10
different laboratory rats
placed sequentially
in the measuring apparatus throughout a
15-minute
period,
all rats being selected or sampled from a common group colony
The target tubes could not be randomized on an individual basis in
the present study due to the nature of one of the experimental questions
(i e
the “few-versus-many-tubes” IDS question), which required mul-
tiple’ trials during a prolonged “effort” period, and therefore a blocked
design. The order of the blocks (PCCP or CPPC) was randomized m order
to control for any time-correlated systematic error.
3.
Factors (e.g., temperature changes, handling differences, etc.) that
might influence hemolysis rate were identified during the pilot and inter-
mediate phases of the study and were eliminated or controlled so that they
were no longer present or active in the formal experiment.
4.
Before the formal experiment began, numerous test runs were con-
ducted that involved multiple tube measurements under conditions iden-
tical to those of the experimental tests, but in the absence of psi influence
attempts. Such tests indicated that the tubes displayed independent activi-
ties over time periods as long as those required for the completion of 20
trials. Inspection revealed no obvious trends or dependencies in the tube
data. Furthermore, autocorrelation coefficients were calculated for all tube
sets of this preexperiment series for which at least 20 sequential tube mea-
surements were available. None of these autocorrelation analyses, each
carried out for lag numbers
1 through 10, provided evidence for trends or
Jessica Utts (personal communication, June
, 1988) indicated that a
positive correlation of the hemolysis values across time would inflate the t
tests. Although indicating that there was no easy way to check for tube
independence, she did calculate correlation coefficients of hemolysis rate
versus the numbers
1 through
10,
for each of the 64
sets of tubes (32
control sets and 32 protect sets) for which she was supplied the raw data.
She reported that the results showed an average correlation of - .03 for
the control sets and - .001
for the protect sets; this indicated that there
was no obvious trend or dependency.
Taken together, these various findings and considerations are more con-
sistent with an assumption of trial (tube) independence than with one of
trial (tube) dependency within time blocks.
A different statistical issue was raised by a referee who inquired as to
whether the data were sufficiently close to normality to justify the use of t
tests. Utts (personal communication, June
1,
1988),
in checking the he-
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