# Linking Data Collection to Causality - PowerPoint PPT Presentation

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## Linking Data Collection to Causality

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### Linking Data Collection to Causality Collecting for a Causality When we collect data, we have varying purposes. Sometimes we just want to describe a population. – PowerPoint PPT presentation

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Title: Linking Data Collection to Causality

1
2
Collecting for a Causality
• When we collect data, we have varying purposes.
Sometimes we just want to describe a population.
• Other times we want to determine whether
variables are causally related.
• When measuring phenomena, the timing and whom we
contact should match our objectives Describe or
Explain.
• How does timing and whom we contact (design)
affect ability to make causal statements?

3
Collecting for a Causality
• X Y
• Independent Dependent
• Variable Variable

Y
X
z
Z
One thing causes another when there is a)
Associationwhen X and Y change in tandem b)
Time Orderfor X to cause Y, value of X must
occur prior to value of Y c)
Nonspuriousnessrelationship between X and Y is
not coincidental or
caused by changes in a third variable (z)
4
Collecting for a Causality
• Cross-Sectional Design
• Collecting data at one point in time, using same
questions only during a single limited
time-frame.
• Great for descriptive work.
• Effect on Causality 1. Can establish
association,
• 2. Time-order is hard to establish
• Answers on variables such as sex and race can be
assumed to have pre-dated answers on other
variables
• Answers to many variables, however, do not
• We often rely on respondents memories to
establish time order and this can be erroneous
(why?)

5
Collecting for a Causality
• Longitudinal Designs
• Collecting data, using same instrument for
everyone, at more than one point in
timeobserving or asking questions across time,
typically at discrete points.
• Works for description over time.
• Effect on Causality Depends on design, trend or
fixed-sample design?

6
Collecting for a Causality
• Longitudinal Designs
• Repeated Cross-Sectional Designs or Trend Studies
• New sample used to collect data at each new time
point.
• Political Polls, General Social Survey.
• Descriptive Can see change over time.
• Effect on Causality
• 1. Can establish association at distinct times.
Cannot establish association at the individual
level over time points. May establish macro
level association over time points.
• 2. Like cross-sectional design at each time
point. Cannot establish time order at the
individual level over time points. May establish
macro level time order over time points.

7
Collecting for a Causality
• Longitudinal Designs
• Fixed-Sample Panel Design or Panel Study
• Same sample used to collect data at each new time
point.
• Descriptive Can see change over time.
• Effect on Causality
• 1. Can establish association at distinct times,
at the individual level over time points, and at
the macro level over time points.
• 2. Can establish time order at the individual
level over time points and at the macro level
over time points. An independent variables
value at a previous time can be linked to a
dependent variables value at a subsequent time.
• Very time-consuming, expensive.

8
Collecting for a Causality
• Non-Spuriousness
• Cross-sectional and longitudinal designs cannot
establish that associations are not spurious.
enough of the right variablesallows one to take
into account other extraneous variables.
• Can you establish nonspuriousness with your
papers analyses?

9
Collecting for a Causality
• Experiments
• Treating groups differently, but collecting the
same information from them.
• True experiments have
• At least two comparison groups (experimental and
control)
• Random assignment of subjects to comparison
groups.
• Variation (or manipulation) in an independent
variable before assessment of outcome on the
dependent variable

Independent Variable
Dependent Variable
Experimental Group
Vary a condition, X
Measure Y
Random Assignment
Compare scores
Sample
Control Group
Measure Y
Do nothing, X
10
Collecting for a Causality
• Experiments
• Devised to assess causality by controlling
everything possible while allowing for a change
in just one variable to see how it would affect
variables of interest in subjects.
• Control is created by randomly placing persons in
two or more groups and treating them the same
except
• Time-order is established by manipulating an
independent variable between groupschanging just
one thing for one group but not the other.
• Association is determined by observing change in
the dependent variable after allowing only the
independent variable to vary.
• Non-spuriousness is determined by not allowing
anything else to vary between groups. If nothing
else is changing, there is no extraneous variable
influencing those of interest.
• Random assignment (NOT RANDOM SAMPLING) of
persons to comparison groups eliminates
possibility of systematic variation between
groups.

11
Collecting for a Causality
• Experiments
• Sometimes, pretests are used prior to
manipulation of the independent variable.
• This does not establish causality as much as it
provides a baseline allowing one to determine
just how much the dependent variable changes
• and can demonstrate similarity of comparison
groups prior to manipulation.

Pre-Measure Y
Independent Variable
Dependent Variable
Experimental Group
Vary a condition, X
Measure Y
Random Assignment
Compare scores
Sample
Control Group
Measure Y
Do nothing, X
12
Collecting for a Causality
• Experiments
• Sometimes, matching of subjects influences
assignment. This is so that one can guarantee
similarity along certain dimensions across
comparison groups.
• If using matching alone, the design is quasi
experimental, quasi meaning something that
appears to be something it is not
• Matching can be used with random assignment

Independent Variable
Dependent Variable
Matching
Experimental Group
Vary a condition, X
Measure Y
Random Assignment
Compare scores
Sample
Control Group
Measure Y
Do nothing, X
13
Collecting for a Causality
• Experiments are good when one can control and
manipulate.
• Experiments are much more common in the natural
sciences
• Sociologists rarely use experiments,
generalizeability for complex social phenomena is
limited
• Ethical concerns lead us to observe rather than
control and manipulate (we just cant control the
way wed have to)
• Control is artificial, setting up
nonrepresentative contexts
• Observation changes the observed, especially
among humans
• Variables of interest are more complex than can
be represented in a controlled setting
• Subjects forming the sample are typically

14
Collecting for a Causality
• Quasi-Experiments
• Quasi-experiments attempt to adapt good things
about experiments to situations where controlled
experiments are impossible.
• Helpful if it is impossible to randomly assign
people to groups that determine their
experienceslike when studying real-world
situations or interventions
• They are common in evaluation researchdetermining
whether an intervention is effective.
• Missing typically is Random Assignment to groups.
• Technically, groups should be determined prior to
manipulation of the independent variable or
intervention.

Independent Variable
Dependent Variable
Experimental Group
Vary a condition, X
Measure Y
Random Assignment
Compare scores
Sample
Control Group
Measure Y
Do nothing, X
15
Collecting for a Causality
• Quasi-Experiments
• Nonequivalent control group designs A ?T-O ?
N-S ?
• Individual Matching
• Persons are assigned to different groups in
pairs so that experimental and control groups
will be similar.
• Aggregate Matching
• Another group of persons that resembles the
experimental group is selected to act as the
control group.

matching
Independent Variable
Dependent Variable
Experimental Group
Vary a condition, X
Measure Y
Random Assignment
Compare scores
Sample
Control Group
Measure Y
Do nothing, X
16
Collecting for a Causality
• Quasi-Experiments
• Before-and-After designs A ?T-O ? N-S ?
• 1. A group acts as its own control. A pretest
measure (the control) is compared with a posttest
measure.
• The control group becomes the experimental group
and is then compared with itself.
• Helpful when a control group is almost impossible
to create or find, such as when an entire
organization changes procedures.

Independent Variable
Dependent Variable
continue
Experimental Group
Vary a condition, X
Measure Y
Random Assignment
Compare scores
Sample
Start here
Control Group
Measure Y
Do nothing, X
17
Collecting for a Causality
• Quasi-Experiments
• Before-and-After designs
• 2. Comparing multiple groups that experience the
same independent variable manipulation improves
Repeated measurement prior to and after change in
the independent variable provides even more
evidence for causality and permits analysis of
how long effects last.

Independent Variable
Dependent Variable
continue
Experimental Group
Vary a condition, X
Measure Y
Random Assignment
Compare scores
Sample
Start here
Control Group
Measure Y
Do nothing, X
18
Collecting for a Causality
• Nonexperiments
• These lack some key element of experiments such
as lacking random assignment to groups, lacking
matching prior to manipulation of the independent
variable or lacking comparison groups.
• Ex Post Facto Control Group Design A ?T-O ?
N-S ?
• The groups cannot be determined in advance, so
there is the possibility of extraneous factors
determining group membership.
• This is often necessary when studying events that
have occurred or practices that are already in
place.

Experimental Group
Vary a condition, X
Measure Y
Compare scores on Y
Find another similar group.
Control Group
Measure Y
Do nothing, X
19
Collecting for a Causality
• Factorial Surveys A ?T-O ? N-S ?
• A research bright spot where researchers
attempt to combine generalizability of a random
sample with random assignment to groups.
• Randomly selected participants randomly get
treatment or no treatment in the survey,
typically vignettes, and then dependent variable
is measured later.
• Often survey methods are tested this way, with
randomly selected sample being randomly surveyed
with different techniques such as with interview,
paper/pencil, or web-based.
• The biggest issue is typically that only
attitudes can be measured, not particular
behaviors.

Independent Variable
Dependent Variable
Experimental Group
Vary a condition, X
Measure Y
Random Sample
Random Assignment
Control Group
Measure Y
Do nothing, X
20
Collecting for a Causality
• A Note
• Regardless of the research method you employ, you
should be thinking in terms of
• Association
• Time-order
• Nonspuriousness

21
Collecting for a Causality
• Some other things to consider, threats to
determining causality and validity. Make sure
you study these.
• Selection bias
• Differential attrition
• Endogenous Change
• Testing
• Maturation
• Regression Effect
• External Events
• Contamination
• Treatment Misidentification
• Researcher demand
• Self-fulfilling prophesies
• Placebo effect
• Hawthorne effect

22
Collecting for a Causality
• In-class Group Assignment (worth 2 Q A)
• The Fantasy Island Preservation Society has
offered you a lot of money to do research. They
believe that watching Fantasy Island increases
willingness to pursue dreams.
• Your job is to devise an experiment that is
reasonably feasible that will determine whether
watching Fantasy Island affects pursuit of
dreams.
• Due at the end of class!