ANECDOTAL
EVIDENCE
Every
time a student of astrology or an astrologer looks
at the astrological birth chart of a person and compares
the information provided in the birth chart and the
person’s life, research is being conducted. Every
time the astrologer looks at the current positions
of the planets and compares them to a person’s
birth chart and notes the events in the person’s
life, research is being conducted.
However,
this kind of research is prone to several problems.
There is selection bias, which means that these charts
are not representative of some larger population of
charts. For example, suppose I do the astrology charts
of friends and family, or suppose that I am a professional
astrologer and most of the charts I do are of clients.
Suppose also that I find that in these charts there
are many cases of Uranus on the 7th house cusp and
people having sudden breakups in relationships. Suppose
also that most of my clients are women over the age
of 40 years old and have no children and they are American.
Can I generalize my findings to men, to women in other
countries, to younger women, to women more affluent,
less affluent, better educated, or more poorly educated
than my clients? Can I even generalize to most women
in the community in which I live, given that my clients
tend to have certain belief systems, life styles, etc.
If the correlation exists, why does it exist? If we
have an idea of the mechanism by which astrology functions,
it may help us to better guess what population we can
generalize to.
Another
big problem is that the belief that Uranus on the 7th
house cusp is associated with breakups in close relationships
is based on a very crude and subjective measurement.
Are we noticing this correlation because we expect
to see it and have we evoked this information from
our clients and do we selectively perceive this event
because we expect to see it? Do we bias our perceptions
by interpreting any breakup as support for our belief,
and do we rationalize breakups of other people as being
less severe than they really are.
For
example, imagine this conversation with a client
who has Venus in Capricorn trine Saturn:
Client: I
am having a consultation with you because I just
went through a divorce with my husband and I am
very upset, and I need to talk to someone.
Astrologer: Were
you married for a long time?
Client: Yes,
20 years.
Astrologer: And
you trusted him and trust is very important to
you. You expect loyalty in a relationship and you
are loyal. Why did you divorce?
Client: I
found out that he was having an affair. And you
are correct. It is the issue of loyalty and faithfulness
that is at the heart of this. I always thought
we would be married until one of us died.
Astrologer: Yes,
the Venus in Capricorn trine Saturn in your chart
shows how important a lasting, loyal relationship
is. You must feel devastated.
Client: I
do. You are so incredibly accurate and this is
really helpful. It is really my sense of loyalty
and dedication and wanting commitment that is so
important to me.
Astrologer: Yes,
exactly! You are using the words that describe
this planetary configuration.
Now
imagine this conversation with a client who has
Uranus conjunct the 7th house cusp:
Client: I
am having a consultation with you because I just
went through a divorce with my husband and I am
very upset, and I need to talk to someone.
Astrologer: Were
you married for a long time?
Client: Yes,
20 years.
Astrologer: Wow,
that is a long time. I mean it’s a long time
given this sensitive astrological influence in
your chart. There is this issue of freedom and
a kind of rebelliousness and irresponsibility that
we think of as something that teenagers are inclined
to, but it can happen in your relationships.
Client: Well,
my ex-husband was always a little less responsible
than me. When we go out he tends to drink, not
excessively, but enough to be dangerous when driving,
and he always thinks he is fine and can drive,
but I have to take the car keys from him and drive
him home or he would be out driving drunk.
Astrologer: Like
a self-willed and irresponsible teenager!
Client: Yes,
(laughs). That’s Joe, a big lawyer who makes
lots of money but never grew up emotionally.
Astrologer: But
still, even though he never grew up emotionally,
you were shocked by his affair?
Client: Yes,
completely shocked.
Astrologer: These
kinds of upsets in relationships are indicated
in your chart, but I am going to give you some
pointers on how to avoid this.
Client: Oh,
thank you so much. You are describing my situation
so precisely. I also had a huge breakup with a
boyfriend when I was 17 years old and I don’t
want to go through this again.
The
astrologer is having a very sensitive and deep conversation
with the client that is very helpful. In this hypothetical
scenario, however, both conversations could happen
with the same client. Amazingly, it is even possible
that the astrology chart served as a guide to help
the astrologer identify issues in the relationships
even if the astrology chart was calculated for the
wrong person! Why was the astrologer correct when surmising
that the breakup was a complete shock, even if the
client did not actually have Uranus conjunct the 7th
cusp? It might be intuition, or an unconscious realization
that the breakup must have been a shock for the client
to schedule the appointment, or it might be some kind
of divinatory process that can occur in consultations
that is not completely understood, but could be classified
as a kind of intuitive or psychic phenomenon. The astrological
language is so profound and so descriptive of the human
situation that it may somehow serve to act as a guide
to help astrologers even though there is no direct
measurable relationship between the astrological variables
and the human behavior. Although it may seem a bit
far-fetched that astrologers can provide helpful and
accurate information to clients without the astrological
variables actually accurately describing a person in
an objective sense when used outside of the context
of the astrological reading, this is an idea proposed
by astrologers, not just by non-believers in astrology.
The
casual or uncontrolled observations that astrologers
and students of astrologers make typically can be classified
as anecdotal evidence. There is no rigorous control
of either how the data is obtained or how the data
that is correlated are measured when anecdotal evidence
is gathered. Anecdotal evidence, however, is not completely
useless. Understanding must begin somewhere and anecdotal
evidence is a starting point. Anecdotal evidence can
also suggest relationships that are later studied in
more detail.
We
have only skimmed the surface of problems with anecdotal
evidence. Developing good research designs is often
a complex process because of the many issues that can
arise. For this reason, academic research is usually
conducted with feedback from content and methodology
experts in a constant attempt to be aware of issues,
problems, and weaknesses in the research design. No
research design is perfect! Research is a pragmatic
enterprise where one does the best that one can given
the problem being tackled and the resources available.
When astrology is studied in a more controlled
environment where the population being generalized to
is clearly stated, the charts are sampled from this population
in a reasonable way, and some form of clear measurement
of a trait is used to correlate with an astrological
factor, rarely has a statistically signfiicant correlation
been found, and when it has been found, it has not been
consistently replicated to the satisfaction of all experts
who have studied the research. There have been studies
such as the studies by Michel Gauquelin that show promising
results, but no study has been consistently replicated,
so whether astrology actually works in a kind of scientific
and measurable way is still not known and there is no
solid evidence that it does. There are, however, some
promising studies that suggest that there might be a
measurable effect, so a raging debate continues as to
whether quantitative research in astrology is even a
wortwhile endeavor.
QUALITATIVE
RESEARCH
The
failure of quantitative research in astrology to produce
findings that support astrology has inclined some astrologers
to feel that astrology may lie outside the boundaries
of a science that can be studied with these kinds of
research methods, but qualitative research studies
are still useful and informative. Qualitative research
is an important research method regardless of one's
attitude towards quantitative research. Qualitiative
research can help understand the meaning of astrological
variables but does not prove that astrology works,
so it may be more important to astrologers than to
skeptics of astrology.
Qualitative
research does not attempt to quantify findings and
establish a measurable effect of some astrological
variable in a quantitative manner. In qualitative research,
numbers and statistics may be used but the conclusions
are not based on the assumption that observations can
be reduced to numerical values and compared based on
these numerical values.
Table
1: A comparison
of qualitative and quantitative designs according
to one researcher:
Quantitative
|
Qualitative
|
Both
are systematic in their approach
|
Objective
|
Subjective
|
Deductive
|
Inductive
|
Generalisable
|
Not
generalisable
|
Numbers
|
Words
|
Note: Table
1 is from http://www.fortunecity.com/greenfield/grizzly/432/rra2.htm and
downloaded on September 24 2011.
Another
comparison of qualitative and quantitative research
is given in Table 2 according to another researcher.
These tables give a good sense of the differences between
qualitative and quantitative research. Note in Table
2 the difference in the goals of the investigation.
Qualitative research focuses on understanding and description,
while quantitative research attempts to predict or
confirm a hypothesis.
Table
2: Characteristics of Qualitative and
Quantitative Research
Point
of Comparisons
|
Quantitative Research
|
Qualitative
Research
|
Focus
of research
|
Quality
(nature, essence) |
Quantity
(how much, how many) |
Philosophical
roots
|
Phenomenology,
symbolic interaction |
Positivism,
logical empiricism |
Associated
phrases
|
Fieldwork,
ethnographic, naturalistic, grounded, subjective |
Experimental,
empirical, statistical |
Goal
of investigation |
Understanding,
description, discovery, hypothesis generating |
Prediction,
control, description, confirmation, hypothesis
testing |
Design
characteristics |
Flexible,
evolving, emergent |
Predetermined,
structured |
Setting |
Natural,
familiar |
Unfamiliar,
artificial |
Sample |
Small,
non-random, theoretical |
Large,
random, representative |
Data
collection |
Researcher
as primary instrument, interviews, observations |
Inanimate
instruments (scales, tests, surveys, questionnaires,
computers) |
Mode
of analysis |
Inductive
(by researcher) |
Deductive
(by statistical methods) |
Findings |
Comprehensive,
holistic, expansive |
Precise,
narrow, reductionist |
Merriam, S.B. (1988). Case study research in education: A qualitative approach.
San Francisco: Jossey-Bass, p. 18.
Note: The
above table and reference is from http://www.okstate.edu/ag/agedcm4h/academic/aged5980a/5980/newpage21.htm
and was downloaded on September 26, 2011.
There
are many kinds of qualitative research designs, and
I will not attempt to discuss them here. This short
introduction to research methods is designed to simply
orient you to the basic directions for research without
going into any detail.
EXPLORATORY
RESEARCH
Some
research designs are not hypothesis tests and do not
attempt to answer a specific question. A hypothesis
test attempts to find an answer to a question such
as “Do people with stelliums in Cancer in the
4th house more likely to work in an area involving
domestic products, homes, real estate, children, or
stay at home to work than other people?” In exploratory
research we explore the data to see what relationships
exist in the data. Sometimes hypothesis tests can be
done later based on the findings of the exploratory
research. Exploratory research might investigate what
astrological factors occur in the charts of scientists,
musicians, painters, and other professions, and then
based on these findings develop a hypothesis to be
tested. Exploratory research is prone to find many
relationships that are not replicable findings because
the findings are just random occurrences in the data
that is sampled, but if done properly, exploratory
research can also help discover relationships that
can be replicated in future studies.
Note that some astrological studies are
exploratory but are then are incorrectly used as strong
evidence in favor of astrlogy. This is especially a problem
when no strong theoretical justification for the findings
is given. For example, periodically a study is reported
where certain sun signs are found to be more likely to
be in particular professions or to differ in some other
way. However, these studies typially are exploratory.
In an exploratory study one does not state a clear hypothesis
before the data is collected. Furthermore, one does ot
restrict observations to those that fit one's expectations
based on previous studies and/or a clear theoretical
framework. In order to draw a conclusion that there is
a corelation of the astrological variable and the behavior
measuerd, one must also consider the possibility of confounding
variables that may exist given that the study is not
an experimental design. This problem is discussed below.
DESCRIPTIVE
RESEARCH
Surveys are often conducted simply to be
able to describe a situation. We may wish to know how
many people in a given community or urban area hold a
certain political position, preference, or interest.
This can be useful to people who may wish to open businesses
or plan future development for a community. Descriptive
research is generally not a kind of research that astrologers
pursue. What may seem like descriptive research is usually
actually exploratory research to determine relationships
of astrological variables and behavior in order to study
these relationships in more detail in the future. Because
descriptive research is a common kind of research study
and is very important in other disciplines, it is worthy
of mention in this introduction to research designs,
and it is possible that some astrologers will engage
in descriptive research to understand more about a particular
population being studied or for some other reason.
QUASI-EXPERIMENTAL
DESIGNS, EXPERIMENTAL DESIGNS, AND NATURAL EXPERIMENTS
In
an experimental design treatment is controlled. The
word “treatment” is used loosely to mean
the predictor variables (Experimental and Quasi-Experimental
Designs by Shadish, Cook, and Campbell, 2002, page
12). In astrology the treatment is the astrological
factors such as planets in zodiac signs, house, or
in aspect. The researcher does not control these astrological
influences; we cannot manipulate them. The astrological
factors are naturally occurring effect and is referred
to as a natural experiment (Shadish, Cook and Campbell,
2002, page 12).
Quasi-experimental
designs are an area of very interest and research in
recent years. In a quasi-experimental design the treatment
is done through self-selection rather than random assignment.
A study of the relationship of smoking and lung cancer
is typically done as a quasi-experiment. People self-select
to smoke. We cannot randomly assign people to smoke
and then see if they get cancer.
Although
drawing causal inferences from quasi-experimental studies
is difficult, it is not impossible. Donald Rubin’s
potential outcomes framework (very often referred to
as the counterfactual framework but Rubin’s preferred
term is potential outcomes framework). The essence
of the potential outcomes framework is whether the
occurrence of event B depends on whether event A occurs.
The potential outcomes framework eliminates the complex
philosophical issues of mechanisms that are regarded
as causal and simply replaces the idea of causality
with a question of whether a particular behavior occurs
dependent on some other earlier behavior.
Rubin's
potential outcomes framework views causal inference
as a kind of missing data problem. We
may observe, for example, that smokers more often have
lung cancer than non-smokers. The data that we do not
have is whether the person would have lung cancer if
he/she had not smoked. Data from people who do smoke
does not provide this missing data because the non-smokers
may differ in many ways from smokers. The non-smokers
may not only avoid smoking, they may also avoid excessive
alcohol, may exercise more, may differ in age, education,
race, gender, urban/rural place of residence, region
of the country, emotional well-being, etc. These variables
are referred to as covariates and they are referred to
as confounding variables if they influence outcome (lung
cancer) as well as are correlated with treatment (smoking
/ non-smoking). A confounding variable may be the cause
for boh treatment and outcome and thus invalidate any
causal relationship between smoking and lung cancer.
Not that we are using the word "causal" as
it is used in the counterfactual framework, as indicating
whether one behavior (lung cancer) occurs if another
behavior (smoking) occurs. This use of the word causal
removes issues of how this causal relationship exists;
it does not need to occur through some kind of Newtonian
model of material causality such as in the laws of motion
and inertia.
Researchers have devised many elegant mathematical
models and research methods to assist in drawing causal
inferences in quasi-experimental designs. One breakthrough,
for example, is the use of propensity scores to balance
the treated and untreated groups. A propensity score
is the measurement of treatment assignment given the
covariates. Several matching mathematical algorithms
have been developed to match the groups based on propensity
scores and relatively new methods such as data mining
methods such as boosted regression have been applied
in simulation studies to determine if they provide more
accurate estimates of propensity scores than with the
moer traditional methods such as logistic regression.
These are very hot areas of reseach now because improving
the ability to draw causal inferences (as defined according
to the potential outcomes framework) is vitally important
especially in the social sciences.
I have gone into some detail in describing
Rubin's potential outcomes framework because it is central
to current research in quasi-experimental designs, and
quasi-experimental designs, like the natural experiments
that astrologers frequently use when conducting research,
share a common problem of not having the advantages of
a randomized experiment. In a randomized experiment,
covariates that are potential confounders are also randomly
distributed among the experimental and control groups
so causal inference is much easier in a randomized experiment.
However, like medical researchers studing the relationship
of smoking to cancer, we cannot randomly assign people
to have different astrological variables and see what
the resulting behavior would be if everything else remained
the same. Like medical researchers and social science
researchers, however, we can do the best we can given
these realities.
Quasi-experiments
and natural experiments are similar in many respects.
In both cases we can ask the counterfactual question
of whether the outcome variable occurs dependent on
the predictor variable. In the case of astrology, we
ask the question of whether an outcome, such as talking
a lot (which can be measured as the number of words
spoken in a day) is related to the predictor of planets
in Gemini. Although some astrologers might argue that
astrology works through synchronicity and Gemini does
not cause talking, that is not relevant to the potential
outcomes framework. We simply ask the counterfactual
question of whether the person would talk a lot of
the planets were not in Gemini, and if we can answer
this question, then a causal relationship exists even
if that causal relationship is through some kind of
synchronistic mechanism. In the potential outcomes
framework causality is not restricted to causality
in the sense of Newtonian laws of inertia as material
causes. Because planetary positions are determined
by mathematical formulae and are not influenced by
human behavior, the astrological variable is the predictor
variable (also referred to as the treatment in some
of the literature) and the human behavior is the outcome
variable.
CONDUCTING
ASTROLOGICAL RESEARCH
Any
of the major astrology programs can calculate charts
and save them in a database to be analyzed for research.
If you are unsure if your software can conduct the
research you would like to do and you cannot figure
it out from the Help or documentation provided with
the program, then contact the software manufacturer
for help. I am one of the authors of the Kepler and
Sirius software programs and I use this software in
all of my research. With over 40,000 charts included
with Sirius, including the Gauquelin database as well
as company data and data for famous people, and the
extraordinary range of research features provided,
one can implement an enormous number of research designs
with this software. I continue to add more features
as I and other users conduct research that requires
additional features.
Because
astrological research is usually a natural experiment
rather than a randomized experimental design, how do
we deal with the problem of possible confounding variables
in quantitative research designs? The most common confounding
variables are cyclic or social causes of a distribution
of the astrological variables in the group being studied
that is different fron the distribution that we had
anticipated.
For
example, suppose you do a study of some particular
group of people and you find that many of them
have Sun in Taurus and Aries rising, which is a
combination that I happen to have in my chart.
Actually, there are some seasonal variations in
some countries and birth in the Spring is sometimes
more common so Sun in Taurus may be an artifact
of being born in the Spring season. How about Aries
rising? Some studies have shown that with natural
births, there is a greater tendency for birth to
occur before sunrise. (Sorry, I have not looked
up the references of these studies, but I am using
them primarily for didactic purposes here). So
Aries rising is common as well.
However,
in hospitals where there are a large percent of births
through operation, more babies are born during office
hours of 9 AM to 5 PM! The cyclic motion of planets
is complex and in some years particular aspects occur
more often than others. Consider also that births often
peak in communities 9 months after large numbers of
military troops return home (perhaps this would not
occur if half the military were women). Some studies
also indicated a rise in births 9 months after snow
storms or holidays provide couples the opportunity
to spend more time being intimate. Even without these
social causes of varying birth rates and thus varying
disributions of astrological variables, the complexity
of planetary motions can result in unexpected varying
distributions of planetary configurations.
An
interesting example of confounding effects that I encountered
was in a strudy of introversion/extraversion. While
analyzing the data I noticed an effect on introversion
by outer planets. At first, I felt excited as it looked
like I was on the track to finding a measurable effect
from an astrological variable. Later it occurred to
me that perhaps these outer planet placements were
different for older people in the study and perhaps
older people are more introverted. Thus, age would
be the confounding variable. I analyzed the data and
this proved to be true.
Furthermore,
a search in academic journals of articles on the relationship
of age and introversion produced papers that showed
a positive correlation of age and introversion. My
study confirmed these findings and perhaps this study
will be of equal interest to academic rsearchers of
the relationship of age and introversion as to those
interested in astrological research. I reanalyzed the
data including age as a variable using a structural
equation model, and the results showed an extremely
strong effect of age (p<.001) and also a significant
astrological effect (p<.02). (http://astrosoftware.com/articles/GauqPaper2/GauquelinPaper2.htm)
I
present this study as an example of the ways in which
the concepts being presented in this paper are very
real and important issues that you can encounter in
actual rsearch. Also, this story gives a sense of the
experiences one can have while conducting research
in which one is sincerely trying to learn how astrological
variables may work rather than superficially engaging
in research either to support one's previous beliefs,
whether they are pro-astrology or anti-astrology. The
search for a measurable astrological effect can be
a rocky road of joyful hopeful results and depressing
findings, but I do learn a great deal about how astrology
works in every study that I conduct, and these findings
complement and augment the understanding gained through
less controlled astrological study and research. Still,
the goal of quantitative research of a replicable measuable
astrological effect eludes us.
In
astrological research, we generally try to make sure
that the groups we are comparing cannot have varying
distributions of the astrological variables as a consequence
of confounding variables. One must consider varous
possible cyclic and social effects on the distributions.
There are also ways to simulate control groups. Propensity
scores and other balancing scores that are used in
quasi-experimental designs are not likely to be as
helpful for astrological research as they are in many
quasi-experimental designs. I will not discuss these
issues in detail here because this subject is a large
one and can be the subject of a separate paper.
In
my own research in harmonic astrology, there is an
advantage that higher harmonics tend to be fairly evenly
distributed across relatively short periods of time
so that there is less likelihood of the effects of
confounding than there is for the occurrence of conjunctions
and oppositions, for example. However, there are not
guarantee prophylactics against confounding variables
or statistical aberrations. Research takes time and
most discoveries emerge gradually as replications and
variations of studies are conducted rather than in
a single eureka-like moment of discovery.
Some
additional guidelines for conducting research are given
at the beginning of a paper at http://astrosoftware.com/Proveast.htm.
The 12 guidelines given in this paper can be very helpful
for anyone who wishes to embark on any kind of astrological
research study, whether it be qualitiative or quantitative.
CONCLUDING
REMARKS
Astrologers
embrace many different theories, including Vedic,
Hellenistic, medieval, harmonics, midpoints, modern
psychological,
with almost endless variations within each of these
traditions as well as other traditions. Astrologers
also embrace a great range of theoretical frameworks
regarding how astrology works, such as divination,
motivation, “as above, so below”, energetic
patterns, etc.
There
is also a wide spectrum of research methods that can
be used according to the research questions of interest
to the astrological researcher, the theoretical framework,
and the astrological tradition being evaluated. Research
methodology has evolved rapidly in recent decades with
rapid advancement in methods like multi-level modeling,
structural equation modeling, data mining methods,
etc. as well as tremendous improvements in statistical
software to make analyses feasible. Astrologers can
benefit greatly by employing these methods and this
article is an attempt to introduce a few fundamental
concepts in research methodology that are relevant
to astrological research.
|