The Idea of Causation
“Causal” Research
• If the objective is to determine which
variable might be causing a certain behavior
(whether there is a cause and effect
relationship between variables) causal
research must be undertaken.
Causation
• We are always coming up with explanations for why
things happen: why we got into a particular school and
not into another, why people treat us the way they do,
why we gain or lose weight, why we oversleep.
• When we take the idea of causation seriously, however,
it becomes complex and even threatening.
• Notions of cause and effect that make easy sense in the
materialistic realm of the natural sciences become more
unsettling when applied to human beings.
• In order to determine causality, it is important to hold the
variable that is assumed to cause the change in the other
variable(s) constant and then measure the changes in the
other variable(s).
• This type of research is very complex and the researcher
can never be completely certain that there are not other
factors influencing the causal relationship, especially
when dealing with people’s attitudes and motivations.
• There are often much deeper psychological
considerations, that even the respondent may not be
aware of.
Deterministic View
• To say that X is caused by Y is to say that once Y
has happened, X will follow. X has no say in the
matter, no choice.
• This deterministic view, when applied to human
behavior, flies in the face of our implicit notions
of free will.
– Although we are threatened by the idea that we have no
free will, we also deny our ability to choose every day in
the things we say. "I could never date a boy who
smoked." "I couldn't tell my mother that." We seldom
say, "I choose not to do that."
– Our reasonableness gets us into trouble in this
realm. When you give the reasons for some action, those
reasons become the cause, not your personal choice.
Models of Explanation
• Idiographic model aims at a complete understanding of a
particular phenomenon, using all relevant causal factors
– enumerates detailed/unique factors that lie behind some action or
social fact
• Nomothetic model aims at a general understanding of a
class of phenomenon, using the smallest number of most
relevant causal factors.
The nomothetic model is
probabilistic in its approach to causation. It is the model
typically used in social scientific research.
– isolates the few key characteristics uniting similar cases
An indiographic explanation
• Taking this research methods course
• If you reflect on it, there are probably a number of reasons for
why you are taking this course. Some reasons may be highminded, such as your desire to learn research methods that will
help you save the world and/or your interest in exploring
pedagogical methods. Some reasons may be more mundane:
the course is required, it fit into your schedule.
• If you were to write down thirty or forty of the most important
reasons why you are taking this course, we would feel we fully
understood why you are doing it.
A nomothetic explanation
• If you think about it, however, there are probably a few factors
that would figure into the decisions of most people who are
taking the course.
• A nomothetic explanation offers a partial explanation for the
behaviors of many people.
• Such explanations are not limited to a single case, as
idiographic explanations are: they provide a more generally
applicable explanation.
• The trade-off is that nomothetic
probabilistic, not certain or complete.
explanations
are
Correlation
• Relates to closeness, implying a relationship
between objects, people events, etc.
•For example, people often believe there are more
bizarre behaviors exhibited when the moon is full.
Correlation – Statistically Speaking
• Correlation is a measure of association that tests
whether a relationship exists between two variables.
• It indicates both the strength of the association and its
direction. The Pearson product-moment correlation
coefficient, written as r, can describe a linear
relationship between two variables.
• The value of r can range from 0.0, indicating no
relationship between the two variables, to positive or
negative 1.0, indicating a strong linear relationship
between the two variables.
Establishing Causality
• To establish whether two variables are causally related, that is, whether a
change in the independent variable X results in a change in the dependent
variable Y, you must establish:
• 1) Time order: The cause must have occurred before the effect
• 2) Co-variation (statistical association): Changes in the value of the
independent variable must be accompanied by changes in the value of
the dependent variable
• 3) Rationale: There must be a logical and compelling explanation for
why these two variables are related
• 4) Non-spuriousness: It must be established that the independent
variable X, and only X, was the cause of changes in the dependent
variable Y; rival explanations must be ruled out.
Establishing Causality
• Note that it is never possible to prove
causality, but only to show to what
degree it is probable.
Correlation Does Not Imply Causation
• There is a statistical correlation over months of the
year between ice cream consumption and the number
of assaults. Does this mean ice cream manufacturers
are responsible for crime?
• No! The correlations occurs statistically because the
hot temperatures of summer cause both ice cream
consumption and assaults to increase.
• Thus, correlation does NOT imply causation. Other
factors besides cause and effect can create an
observed correlation.
Necessary versus Sufficient
• A necessary cause represents a condition that must be
present for the effect to follow
• A sufficient cause represents a condition that will
pretty much guarantee the effect
• In social science, evidence of either a necessary or
sufficient cause is often used as the basis for
concluding that a relationship is causal
Examples
• Being female is a necessary condition of being
pregnant.
Being female is not a sufficient
condition, since you can be female without being
pregnant.
• Being convicted of a crime is a sufficient cause of
being judged guilty. It's not a necessary cause,
however, since you could be judged guilty as a
result of confessing to the crime.
• There are seldom absolute cases of either necessary or
sufficient causes and never cases of both.
• Having sexual intercourse, for example, would be
called a necessary cause of being pregnant. It's not
absolute, since you could get pregnant via artificial
insemination. Since the great majority of pregnancies
result from intercourse, however, it makes sense to
call it a necessary cause. It's clearly not a sufficient
cause, since most of the time, intercourse doesn't
result in pregnancy.
Errors In Reasoning
•
Provincialism means that all of us seek to understand in the terms of our past
experiences and culture.
– What makes sense to us may not make sense to others.
•
Hasty conclusions are the explanations we settle on to resolve an issue quickly.
– may make sense, but other explanations we didn't think of might make better sense
•
Similarly, what first seems like a logical cause, may become questionable upon later
consideration.
– Other evidence may make it unlikely.
•
Once we have an initial conclusion about the important causes, we may ignore or
suppress other information as irrelevant
– Could be missing the most important cause
•
Sometimes we fall under the spell of a false dilemma in deciding which of two
possibilities is the true cause.
– Maybe both are causes.