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PSYC 306 > Lecture 21: Non-Experimental and Quasi-Experimental Designs > Flashcards

Lecture 21: Non-Experimental and Quasi-Experimental Designs Flashcards

1
Q

non- and quasi-experimental designs

A
  • In both non- and quasi-experimental designs, there is no manipulation (by the experimenter) of the IV
  • Researchers compare pre-existing groups on a DV of interest
  • Groups are defined by time or participant characteristics
  • Both non-and quasi-designs produce groups of scores to be compared for significant differences
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2
Q

characteristics of non- and quasi-experimental designs

A
  • No random assignment
  • We cannot determine causality
  • Groups can differ on other factors: internal validity issues
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3
Q

research design terms used in quasi- and non-experimental designs

A
  • Quasi-independent variable (IV): the variable used to differentiate the groups of participants or the groups of scores being compared
  • Dependent variable (DV): the variable that is measured
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4
Q

similarities between non- and quasi-experimental designs

A
  • No manipulation of the IV
  • No random assignment
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5
Q

differences between non- and quasi-experimental designs

A

Quasi-experimental uses controls for confounds to keep internal validity high, but non-experimental doesn’t

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6
Q

IV in non- and quasi-experimental designs

A
  • Typically, the IV is a participant variable (age, marital status) or a time variable (pre- or post-event)
  • The researcher usually cannot control the assignment of participants to groups because the groups already exist
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7
Q

3 general categories of non- and quasi-experimental research

A
  • between-groups design
  • within-groups design
  • developmental research design
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8
Q

types of between-groups designs

A
  • Differential design: non-experimental
  • Post-test only NEG design: non-experimental
  • Pre-test/post-test NEG design: quasi-experimental
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9
Q

types of within-groups designs

A
  • One group pretest-posttest design: non-experimental
  • Time series design: quasi-experimental
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10
Q

types of developmental research designs

A
  • Cross-sectional designs: between-subjects 2 or more groups
  • Longitudinal designs: within-subjects 1 group, measured 2 or more times
  • Cross-sectional and longitudinal: between- and within-subjects 2+ groups, measured 2+ times
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11
Q

non-equivalent group (NEG) between-groups design

A
  • Pre-existing groups are used
  • Groups are differentiated by one specific factor
  • The purpose is to show that this factor is responsible for differences between the scores of the groups
  • Called “non-equivalent groups” because the experimenter cannot control the group’s membership (or individual differences)
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12
Q

assignment bias in non-equivalent group (NEG) between-groups design

A
  • These designs raise the problem of assignment bias
  • Groups may differ on a variable other than the IV and this can be a possible confound
  • Precludes cause-and-effect explanations
  • Because of this lack of control, there is a threat to internal validity
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13
Q

differential designs (non-experimental)

A
  • Also called an ex-post facto (after the fact) design
  • Simplest of the between-group (NEG) designs
  • Individual differences are the primary interest: form groups based on these differences
  • Simply compare these pre-existing groups to find a difference in the variable of interest
  • No manipulation of control of assignment of participants to groups; just comparing them on pre-existing characteristics
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14
Q

example of a differential design

A

SES, stress, and cognitive function study found that there were no differences in cognitive functioning between high and low SES groups but there were early stress differences in the younger groups

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15
Q

Post-test-only NEG designs

A
  • Interested in examining the effectiveness of a treatment or intervention (applied research)
  • No manipulation or control over who is exposed to the treatment or intervention
  • Compare those who received treatment vs. those who did not, based on pre-existing groups
  • No control over the assignment of participants to groups; one group is measured after tx, other group is measured at the same time (but received no treatment)
  • Commonly used when tx is given to a cluster of individuals and compared to another cluster
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16
Q

assignment bias in post-test-only NEG designs

A

This method does not address the problem of assignment bias

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17
Q

pre-test/post-test NEG designs

A
  • With this design, we try to add a bit of control by including a pre-test measurement for both groups
  • Much stronger version than the NECG
  • Limits threats to internal validity
  • Can compare groups before treatment and look at differences pre- and post-treatment
18
Q

how can you reduce threats to internal validity in pre-test post-test NEG designs

A
  • Determine how similar the two groups are, before administering treatment by comparing pre-treatment measures
  • If similar at pre-test, there is evidence that Ps in one group is not substantially different from those in another group
  • Although this does not make the groups equivalent, it does reduce the impact of assignment bias on the results
  • With this technique, you are controlling for one specific variable
  • With randomization in a true experimental design, you can target multiple variables
19
Q

what threats are pre-test post-test NEG designs vulnerable to?

A

the same threats to internal validity as experimental designs (history, instrumentation, testing effects, maturation, and statistical regression)

20
Q

how should we interpret the following findings in a pre-test post-test design?: participants are similar at pre-test but there is a post-treatment difference between groups

A

we can be somewhat confident that it is due to the treatment

21
Q

advantage of pre-test post-test NEG designs

A

limit time-related threats

22
Q

one-group non-experimental pretest-posttest designs

A
  • Studies in which a series of observations are made over time in just one group of participants
  • There is no attempt to control threats to internal validity
  • Two observations are made for each participant, one before and one after treatment
23
Q

goal of one-group non-experimental pretest-posttest designs

A

evaluate an intervention/treatment by comparing observations made before with those made after

24
Q

assignment bias in one-group non-experimental pretest-posttest designs

A
  • We are not comparing groups (no control group) but rather individual scores before and after treatment
  • The problem of assignment bias is eliminated
25
Q

downsides of one-group non-experimental pretest-posttest design

A
  • You cannot counterbalance the order of treatment as you can in experimental designs
  • You can’t be sure that a change post-treatment is due to the treatment and not some other factor
26
Q

threats to one-group non-experimental pretest-posttest designs

A

Threatened by time-related factors (history, instrumentation, testing effects, maturation, regression)

27
Q

time-series designs

A
  • Attempt to add some control by making a series of observations for each participant
  • Some observations before and some after treatment
  • Similar to single-case designs
28
Q

Value of repeated pretest and posttest observations within participants:

A
  • Allows researchers to see existing trends in data
  • Identify practice, fatigue, maturation, instrumentation, and regression, since they should be measurable before treatment
  • Allows researchers to observe post-treatment trends
  • Can examine manipulated treatments
  • Can look at non-manipulated events (data from archives) and societal changes
29
Q

how many data points are needed in a time-series design?

A
  • You need at least 3 data points before the treatment and 3 after
  • Multiple observations allow you to see if the change is due to your treatment or not and examine post-treatment trends to see if the effect of X fades
30
Q

threats to internal validity in time-series designs

A
  • An external event can be a threat to internal validity in time series designs but only if it occurs at the same time as the treatment
  • If treatment and outside events occur at different times, one can separate the effects in the time series using statistical techniques
31
Q

cross-sectional developmental research designs

A
  • A between-groups design that uses different groups for each age or age bracket
  • The outcome variable is measured for each group at one point in time and the groups are compared
  • When a study evaluates differences related to age, the design is typically called cross-sectional
32
Q

example of a cross-sectional developmental research design

A

differences in ease of using technology by age group

33
Q

advantages of cross-sectional developmental research designs

A
  • Time-efficient (one measurement time-point)
  • No long-term cooperation required
34
Q

disadvantages of cross-sectional developmental research designs

A
  • Cohort or generation effects (changes due to era or period)
  • Individual changes are not assessed
35
Q

longitudinal developmental research designs

A
  • A within-groups design that measures a variable in the same group of individuals over time
  • Participants have usually grown up in similar circumstances
  • One group’s pretest-posttest measures of health are collected
  • The treatment is age
36
Q

advantages of longitudinal developmental research designs

A
  • No cohort or generation effects
  • Individual changes are assessed
37
Q

disadvantages of longitudinal developmental research designs

A
  • Time-consuming and costly
  • Participant attrition can cause unbalanced measures
  • Potential for practice effects over time (repeated tasks)
38
Q

cross-sectional longitudinal designs

A
  • Also known as mixed developmental designs
  • Compare results that were obtained from separate samples (cross-sectional) that were obtained several times (longitudinal)
  • Allows for the examination of the development of behaviours due to mechanisms other than individual aging
  • Can draw comparisons within groups (across time) and between groups (same time point)
39
Q

example of a cross-sectional longitudinal design

A

influence of sport on physical development

40
Q

Major distinction of non- and quasi-experimental designs from experimental designs

A

no random assignment of participants to conditions

41
Q

Major distinction of non-experimental from quasi-experimental designs

A

no attempt at control comparison in non-experimental designs

PSYC 306 (17 decks)

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