Quant quiz 2 Flashcards

1
Q

Quasi – Experimental Designs

A

Used when control features of experimental
design cannot be achieved

*Independent variable cannot be manipulated, or

*Random assignment to groups cannot be achieved

*Internal validity may be affected

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2
Q

Quasi Example- One-Group Posttest-Only Design

A
  • Lacks a control/comparison group
  • Lack baseline data
  • Difficulty making inferences about the effect of the IV on the
    DV (low internal validity)
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3
Q

Quasi Example- One-Group pretest-posttest design

A
  • Now there is baseline comparison data, but no control/comparison group
  • Threats to the internal validity of these types of studies:
  • History
  • Maturation
  • Testing
  • Instrument Decay
  • Regression towards the mean
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4
Q

Threats- history

A

Refers to any event that occurs between the 1st and 2nd
measurement (not a part of the experiment)

  • Any confounding event that occurs at the same time as the
    experimental manipulation
  • EXAMPLE:
  • change in political leader
  • terrorist attack
  • natural disaster
  • Global pandemic!
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5
Q

Threats- maturation

A

People change over time

  • Short periods of time:
  • Boredom
  • Fatigue
  • Hunger
  • Wiser

Long periods of time:
* Increased coordination
* Increased analytical skills
* Change of priorities/core values
* Life events

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6
Q

Threats- testing

A

Testing may be acting as an
intervention on its own

  • A pre-test may sensitize participant in
    unanticipated ways and their
    performance on the post-test may be
    due to the pre-test, not to the
    treatment,
  • Or, more likely, and interaction of the
    pre-test and treatment
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7
Q

Threats- Instrument decay

A
  • The characteristics of the
    measurement change over time
  • Ex: observation or self-
    monitoring
  • The rater changes their rating
    behavior over time due to any
    number of reasons
  • Scale needs calibration
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8
Q

Threats- Regression towards the mean

A
  • When participants score really high or really low on a
    measure, they are likely to score closer towards the mean
    when retested at a different time
  • Statistically, outliers tend to be less extreme when tested again
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9
Q

Nonequivalent control group
design

A
  • Separate control group, but the participants in the two conditions are not equivalent
  • i.e., they were not randomly assigned so we cannot guarantee equivalence…
  • Selection Difference/ bias
  • The groups are not a result of random assignment but are from existing natural groups
  • Thus, not matter what, are vulnerable to selection bias
  • Example:
  • Treatment group are people who volunteered for treatment and the control group are people who just meet criteria
  • There might be group differences between the groups of volunteers
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10
Q

Nonequivalent Control Post-test
Group Design

A

*Participants are not randomly assigned to groups
*No pre-test

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11
Q

Nonequivalent Control Group
Pretest-Posttest Design

A

*Still not randomly assigned groups, BUT the model
is improved with a pretest
*Not randomly assigned but we can test for some
equivalence using the pretest

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12
Q

Propensity score matching of
nonequivalent treatment and control
groups

A

*Nonequivalent control group problem: groups can
differ in important ways
*Improve with:
* Score matching
* matches one participant from the experimental group with
one person from the control group on potential confounding
* E.g., Age
* Propensity score
* scores on multiple variables are combined to produce a
propensity score and then participants are matched using that
number
* E.g., Age, level of education, ethnicity

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13
Q

Why control/comparison groups,
equivalent or non-equivalent, are so
important

A

Can see if these threats to
internal validity affect the
control group AND the
treatment group!!

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14
Q

Single Case Experimental
Designs

Single Subjects

A
  • Made popular from operant conditioning research (B.F. Skinner)
  • Now used in ABA (applied behavior analysis)
  • Does an experimental manipulation have an effect on a single research participant?
  • You can use this with individual therapy clients to help foster insight into their own patterns. Have them do their own single case experiments to made behavioral changes (stop a bad habit)
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15
Q

Single Case Experimental
Designs

A

*Baseline (A):
*Observed behavior before manipulation
*Treatment (B):
*Introduce manipulation/treatment
*Many measurement timepoints
*Change in behavior from A -> B presumes a
treatment effect

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16
Q

Reversal (or Withdrawal) Design

A

Baseline (A)
Treatment (B)
Baseline (A)

*Minimizes
alternative
explanations when
we see direct change
in behavior

17
Q

Additional Reversal Designs

A

ABAB

18
Q

Multiple baseline design

A

Observe change under multiple circumstances
*Introduce manipulation at different points of time
*Determine if manipulation is the cause of change

*Use when:
*Change might be long-lasting, even with withdrawal of treatment (B)
*Unethical to reverse treatment

19
Q

Multiple baseline designs- across subjects

A

the behavior of several
subjects is measured over
time. For each subject, the
manipulation/intervention
is introduced as different
points in time

20
Q

Multiple baseline designs- across behaviors for a single subject

A

ncrease ADLs by
introducing one by one

21
Q

Multiple baseline designs- Across Situations

A

Same bx, same subject,
different settings
* Home, work, school

Take away: A manipulation is always introduced at a different time, with the expectation
that a change in behavior in each situation will occur only after the manipulation

22
Q

Developmental Designs

A

Studies the ways individuals change as a function of
age

23
Q

– Cross-Sectional method:

A

Persons of different ages are measured at the
same point in time
*Easier and more convenient way to collect
developmental data
*Problem: generational differences

24
Q

– Longitudinal method

A

Same group of people are observed at different times as they age

25
Q

Cohort Effect

A

Effect of group of people born at the same
time, exposed to the same events, and
influenced by the same demographic trends
*i.e., generational effect
* Economic and political conditions
* Music and arts
* Educational systems, and child-rearing practices
*Differences in cross-sectional study may arise
due to cohort effects

26
Q

Longitudinal method

A

Longitudinal method
*Expensive
*Takes longer duration
*Can attribute change to
development
*Additional variables can
be assessed at a later
time
*Cohort effect vs. history

27
Q

Cross-Sectional method

A

Relatively cheap
*Comparisons can be
obtained quickly
*Inferring differences to
developmental change is
challenging
*One time measurement
*Cohort effects

28
Q

Developmental Designs- Sequential method:

A

*Combination of longitudinal and cross-sectional
methods
*Ex: total time of actual observation is 10 years,
not 20, but age is 55-75 years old

29
Q

Quantitative Approaches in
Observational Designs

A

Focuses on specific behaviors that can be
easily quantified
*Uses larger samples
*Assigns numerical values to responses
*Conclusions are based upon statistical
analysis of data

30
Q

To compare: Qualitative Approaches
in Observational Designs

A

Focuses on behavior in natural settings
*Small groups and limited setting
*Data are non-numerical and expressed in
language and/or images
*Conclusions based on interpretations drawn
by the investigator

31
Q

Naturalistic Observation- natural setting

A

*Goals
- Describe setting, events, and persons
- Accurate description, objective interpretation, no prior hypotheses

Aggression outside of bars in a cityHandwashing in public restrooms

32
Q

Naturalistic Observation- data

A
  • detailed notes
    *Maybe video or audio recordings
    *Might interview “informants” for additional
    observations
    *Or might be already occurring documents
    *Primarily qualitative
    *Generate hypotheses to help explain the
    data
    *May supplement with quantitative (like
    demographics)
33
Q

Naturalistic
Observation- issues

A

Does researcher become active participant or observe from outside?
* Participation –open and part of group* Able to remain objective?
* Concealment – going under cover* Reduces reactivity (Hawthorne effect)…
* Ex. Hiding under bed: “Egocentricity” in Adult Conversation

ethics and expectation of privacy

34
Q

Naturalistic Observation
*Limitations

A

Cannot be used to study all issues
*Best for investigating complex social settings
*Understand settings
*Develop theories based on observations
*Less useful when studying well-defined hypotheses under precisely specific conditions
*Hard to do!
*1300 nights, 118 bars, 74 male-female paired observers

35
Q

Systematic Observation

A

Careful observation of specific behaviors in a particular setting
*Each behavior needs to have a good operational definition
*Usually prior hypotheses
*Coding systems
- Video coding
- Tallies
- Time samples

36
Q

Systematic Observation- isses, considerations

A

Methodological issues
*Equipment
*Paper and pencil or audio/video
*Reactivity
*Participants behave differently because they are being observed
*Reliability
*2+ raters of same behavior
SamplingDepends on what you are observing…
*In general, time samples spread throughout day are more accurate than 1 longer

37
Q

Observation: Case Studies

A

*Provides a detailed description of an individual
*Valuable in informing us of conditions that are rare, unusual, or noteworthy
*New disorders/medical conditions
usually start with a case study
*Phineous Gage
*Ken Horne: 1980 San Francisco resident is reported to the CDC with Kaposi’s sarcoma

38
Q

Observational:
Archival Research

A

*Involves using previously compiled
information to answer research questions
* Public records
* Medical records
* Survey archives from other studies
* Written and mass communication records
* Social media?
IRB considerations