Quasi-Experiment Methods Flashcards

1
Q

internal validity in quasi-experiments

A
  • quasi experiments lack full experimenter control over the IV
  • they can have better internal validity and can use methods to rule out threats to external validity
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2
Q

how to prevent selection effects as a threat to internal validity?

A

pretest-posttest design
- are subjects at one level of IV systematically different from subjects at another level of IV?

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3
Q

how to prevent design confound as a threat to internal validity?

A

measuring second variable can help rule out design confounds

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4
Q

how to prevent maturation/history as a threat to internal validity?

A

pattern of results in comparison group can help rule out these threats

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5
Q

characteristics of quasi-experiments

A
  • cannot establish causality
  • researchers take precautions to reduce threats to internal validity
  • eliminates as many alternative explanations as possible
  • lack random assignment to condition
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6
Q

non-equivalent groups

A

participants do not start from the level
they vary systematically from the beginning

experiment:
studying students from public/private schools and their attitudes regarding authority

non-equivalent groups need to be in place because students were not randomly assigned to a school

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7
Q

nonequivalent group design

A

compares 2 non-equivalently groups that are intentionally as similar as possible
1. treatment group
2. control group

group a measure DV -> scores
treatment compare

group b measure DV -> scores
control

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8
Q

pretest-posttest nonequivalent groups

A

comparing before and after treatment that participants were not assigned to

compares 2 non-equivalently groups that are intentionally as similar as possible
1. treatment group
2. control group
* difference between scores before and after treatment is compared across groups

surgery pretest treatment posttest

no surgery pretest treatment posttest
* compare results before and after treatment across groups

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9
Q

interrupted time series

A

treatment in the middle of multiple measurements from DV

take multiple pretest and posttest measurements to asses effects of both treatment and time passing

purpose: eliminate noise before and after data

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10
Q

controlled interrupted time series design

A

observe a non-equivalent control group over the same time period

comparing two sets of data and taking multiple measurements

treatment vs no treatment
*measures multiple DVs before and after treatment

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10
Q

structure of interrupted time series design

A

measure DV - measure DV - measure DV -treatment or intervention - measure DV - measure DV - measure DV
compare
compare average before and after treatment

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11
Q

longitudinal developmental design

A

observe a group of individuals as they age
- time consuming and can be confounded by attrition

looking at maturation itself

measure DV over the course of the participants lifespan

and compare the scores over time

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12
Q

cross sectional developmental design

A

compares different age groups to see how the DV changes with age
internal validity threated by cohort effects (differences due to cohort characteristics rather than development)

group 1 measures dv -> scores
(65+ years old)
group 2 meadures dv -> scores
(18-25 yrs old)

compare scores afterwards

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