Exam 2 Flashcards
What is a Quasi-Experimental Appraoch
must have an IV and DV
cannot randomly assign participants to levels of the IV
Loss of control over the experiment
Types of Quasi-Experiments
- Independent groups (non-equivalent control-groups design)
- Repeated measures (interrupted time-series design)
- Combined: non-equivalent control-groups interrupted time-series design
What are Independent groups quasi experiments
non-equivalent control group design
have a comparison group but no random assignment to condition
What are repeated-measures quasi experiments
interrupted time-series design
Participants/groups are measured multiple times before, during, and after an “interruption” (the event of interest)
what are non-equivalent control-groups interrupted time-series design
The interrupted time-series design with nonequivalent groups involves taking a set of measurements at intervals over a period of time both before and after an intervention of interest in two or more nonequivalent groups.
How are quasi-experimental designs in terms of statistical validity
pretty good, same as experiments
How are quasi-experimental designs in terms of construct validity
can be really good, same as or even better than experiments
How are quasi-experimental designs in terms of external validity
can be really good, same as or even better than experiments
How are quasi-experimental designs in terms of internal validity
not good!
how to controls for selection effects in quasi-experiments
“wait list control”
Likert-style items
Rate agreement of a statmetn on a scale of strongly disagree to strong agree
I am creative
Forced choice items
I am creative
I am uncreative
Semantic differential items
uses opposite adjectives
rate your creativity from
1 = uncreative
7 = creative
Threats to constructs validity of surveys
Problems with survey itself:
* Leading questions
* Limited range of response options
* Double-barreled questions
* Negatively-worded (confusingly-worded!) questions
Problems with how participants may respond:
* Response sets
* Fence-sitting (not an issue for every construct)
* Acquiescence bias (“yea-saying”)
* Social desirability
Doubled-barreled questions
Touches on more than 1 issue, but you can only give 1 answer
Likert Items are for
continuous quantitive variables (interval)
Forced-choice items
Categorical / nominal variables
An ANOVA or a regression is typically prefered to a chi square because
if we can analyze more variance (1 to 7 vs. yes/no), we have a better chance of finding an effect
___ data have less power and precision than ____ data
continuous
If it’s an important construct…
include more than one item
what is an important consideration in survey construction
pay attention to reliability and validity
Bivariate Correlation
How 2 variables (usually scale/continuous but not necessarily) are linearly related; on a standardized scale
coefficient r in a bivariate correlation
quantifies the relationship
-1 to +1
Sign indicates direction
Absolute value indicates strength of association
Correlations are both descriptive and inferential
You can have weak but
significant correlations (mostly a
test of if your N is large enough)
Internal Validity for correlational design
correlational studies have limitations that make it hard to make a causal claim
Construct and statistical validity for correlational designs
both are pretty similar between correlational designs and experimental designs
What three things can influence a correlation
outlier, restriction of range, and nonlinearity
What is face validity?
Does it look like a good measure? Ask experts!
Criterion Validity
Measure predicts some real-world outcome (like an important test/clinical diagnosis etc.)
Convergent Validity
- Measure is more associated with similar measures
- Correlates with things it ought to correlate with
Discriminant (divergent) validity
- Measure is not associated with dissimilar measures (not negatively associated
with; r = 0) - Doesn’t correlate with things it ought not correlate with
