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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
Linking Data Collection to Causality
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
    instruments for everyoneobserving or asking
    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
    clearly precede answers to others
  • 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.
    Breadth of data collectionhaving collected
    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
    recruited, leading to nonrepresentative samples

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
    confidence in conclusions about causality.
    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!
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