Questions From Lectures II Flashcards
Atminimum, howmany variables are there in an association claim?
.An association that involves exactly two
variables.
What characteristic of a study’s variablesmakes a study correlational?
They are measured, not manipulated.
Sketch three scatterplots: one that would show a positive correlation, one that would show a negative
correlation, and one that would show a zero correlation.
.
Sketch three bar graphs: one that would show a positive correlation, one that would show a negative
correlation, and one that would show a zero correlation.
.
When do researcherstypically use a bar graph, as opposed to a scatterplot,to display correlational
data?
. can guess, maybe ask
. most likely if one of the variables is categorical
. most likely not to use it if both variables quantitative
In one ortwo briefsentences, explain how you would interrogate the construct validity of a bivariate
correlation.
.Does the measure have good reliability?
-Test/Retest, Internal Reliability, Interrater Reliability
.Measuring what it intends? What is the evidence for its face validity, its concurrent validity, its discriminant and convergent validity?
-Face/Content Validity
-Predictive/Concurrent Validity
(e.g. Do mothers’ answers to this question correlate with their actual employment history? for maternal employment)
-Convergent Validity
-Discriminant Validity
What are five questions you can ask aboutthe statistical validity of a bivariate correlation?Do all ofthe
statistical validity questions apply the same way when bivariate correlations are represented as bar
graphs?
.What is the effect size?
.Is it statistically significant?
.Subgroups within the sample? Is the relationship spurious? Is there a third variable?
.Are there outliers?
.Is the relationship curvilinear? If slope of pattern is not just a straight line, r does not describe pattern well.
Which ofthe three rules of causation is almost alwaysmet by a bivariate correlation? Which two rules
might not bemet by a correlationalstudy?
.Covariance
.Temporal precedence or internal validity
Give examples ofsome questions you can ask to evaluate the external validity of a correlationalstudy.
.Can the association generalize to other people,
places, and times?
Must consider who the participants were and how
they were selected.
The size of the sample does not matter as much as
the way the sample was selected from its
population
Why can’t a simple bivariate correlationalstudymeet allthree rulesfor establishing causation?
.No time difference between measures!
Explain how longitudinal designs are conducted. Why is a longitudinal design called amultivariate
design?
.Because each measure of one variable at different times is a different variable right.
Like, TvViolence2001, TvViolence2011
AND, TIME is a THIRD variable
So no matter what you do, it will always be multivariate
Identify the three types of correlations in a longitudinal correlational design: cross‐sectional
correlations, autocorrelations, and cross‐lag correlations.
.Cross-Sectional: TvViolence2001 & Aggression2001
.Autocorrelations: TvViolence2001 & TvViolence2011
.Cross-lag: TvViolence2001 & Aggression2011
Interpret different possible outcomesin cross‐lag correlations, andmake a causal inference fromeach
pattern.
.ASK
Explain howmultiple‐regression designs are conducted.Describe in your own words whatitmeansto
say thatsome variable “was controlled for” in amultivariate study.
.LOOK IN TEXT
.Control for: Holding p aotential third variable
steady while investigating the association
between two other variables.
Researchers are asking whether, after they
take the relationship between the third variable
and the outcome (effect) into account, there is
still a portion of variability in the outcome
(effect) that is attributable to the predictor
(cause)
Define dependent variables and predictor variablesin the context ofmultiple‐regression data.How
many dependent variables are there in amultiple‐regression analysis?Howmany predictor variables?
.Criterion: Researchers most interested in understanding or predicting (also called DV in this case)
.Predictor: Used to explain variance in the dependent/criterion variable (also called IV in this case.
.only ONE criterion/dependent variable
.unlimited predictor/independent variables i assume
Identify and interpret data fromamultiple‐regression table and explain, in a sentence, what each
coefficientmeans. What does a significant betamean? What does a nonsignificant betamean?
When you have only one predictor variable in your model, then beta is equivalent to
the correlation coefficient between the predictor and the criterion variable. This SPSS for Psychologists – Chapter Seven 209
equivalence makes sense, as this situation is a correlation between two variables.
When you have more than one predictor variable, you cannot compare the
contribution of each predictor variable by simply comparing the correlation
coefficients. The beta regression coefficient is computed to allow you to make such
comparisons and to assess the strength of the relationship between each predictor
variable to the criterion variable.
Give atleastthree phrasesthatindicate that a study used amultiple regression analysis.
.rl between x & y is negative, even when z IS CONTROLLED FOR
.rl between x & y is negative, INDEPENDENT OF the proportion of z
.rl between x & y is negative, even when z IS HELD CONSTANT
.rl between x & y is negative, and is NOT ATTRIBUTABLE TO THE THIRD VARIABLE OF z, because it holds even when the proportion of z is held constant
What are two reasonsthatmultiple regression designs cannot completely establish causation? Explain
why experiments are superiortomultiple‐regression designsfor controlling forthird variables.
- Even though multivariate designs analyzed
with regression statistics can control for third
variables they cannot establish temporal variables, they cannot establish temporal
precedence. - Researchers cannot control for variables that
they do not measure.
A well-run exp yy erimental study is ultimately more
convincing than a correlational study.
The power of random assignment would make the
groups likely to be equal on any possible third
variable.
A rand i d i t i till th ld domized experiment is still the gold
standard for determining causation.
Multiple regression allows researchers to control for
potential third variables, but only those that they
choose to measure
Explain the value of pattern and parsimony in research.
.An approach which allows researchers to
investigate causality by using a variety of
correlational studies that all point in a single,
causal direction.
-pattern of results best explained by parsimonious causal explanation
-parsimony: simplest explanation of a pattern of data
-several diverse predictions are tied back to one central principle = parsimony
-does not work for a single study
Consider why journalistsmight preferto reportsingle studies,ratherthan parsimonious patterns of
data. What problemsresultsfromthistendency?
.Trying to find news, and flashy headlines
.They usually only report the latest finding.
They selectively present only a part of the
scientific process.
Identify amediation hypothesis and sketch a diagramofthe hypothesized relationship.Describe the
stepsfortesting amediation hypothesis.
TESTING FOR A MEDIATING VARIABLE
Kenny (2008):
1.Test for relationship c.
2.Test forrelationship a.
3.Test for relationship b.
4.Finally, run a regression test, using both the predictor and mediator variables to predict the criterion, to see whether relationship c goes away
OR
test for relationship c, then a, then b
-run regression test
-relationship btw IV and DV should drop significantly or become zero when mediator is controlled for
MULTIVARIATE CORRELATIONAL RESEARCH (look up and understand more if time)
Articulate the difference betweenmediators,third variables, andmoderating variables.
.med: “why are these two variables linked?”
mod: “are these two variables linked the same way for everyone, or in every situation?”
THIRD VARIABLE
internal validity rule, when you can come up with an alternative explanation for the association between two variables, that alternative explanation is the third variable
Give an example of a question you would ask to interrogate each ofthe four validitiesfor amultivariate
study.
.Longitudinal designs help establish temporal
precedence, and multivariate provide evidence
for internal validity
Should interrogate the construct validity (i.e.,
how well each variable was measured) external measured), external
validity (i.e., how well the results generalize),
and the statistical conclusion validity (i e the and the statistical conclusion validity (i.e., the
effect size and statistical significance).
What are theminimumrequirementsfor a study to be an experiment?
.A study in which one variable is manipulated and the other is measured.
In your own words, define the termsindependent variable, dependent variable, and control variable.
.IV = Manipulated in an experiment .DV = Measured .Control = Potential variable experimenter holds constant on purpose
How do experimentssatisfy the three causalrules?
.Temporal Precedence: control which variable comes first
How are design confounds and control variablesrelated?
Design confounds threaten internal validity and vary systematically with the independent variable; control variables establish internal validity and do not vary at all. If you can identify a potential design confound and eliminate it by keep that factor constant instead (turning it into a control variable) then you would have more confidence that your independent variable actually caused the difference in your dependent variable.
Describematching, explain itsrole in establishing internal validity, and explain situationsin which
matchingmay be preferred to randomassignment.
Matched-subjects design, participants matched into blocks on the basis of a variable the researcher believes relevant to the experiment. Helps eliminate selection effects, or one condition varying systematically in a way tha is different from the other condition
Describe how the proceduresfor between‐subjects and within‐subjects experiments are different.
Explain the pros and cons of each type of design.
The principal advantage of a within-groups
design is that it ensures that the participants in
the two treatment groups will be equivalent.
As a result, the only difference between the two
groups should be attributable to the
independent variable, not to individual or
personal variables. also INCREASED POWER (ability to detect stat sig effect)
Describe how posttest‐only and pretest/posttest designs are both between‐subjects designs. Explain
how they differ, and when a researchermay use each one.
.With random assignment (posttest only), any preexisting
differences between participants should be
distributed evenly across both groups, and their
effect canceled out.
In some cases, participants might become
suspicious if they are asked to complete the
same thing twice.
The pretesting step is useful if researchers
want to be extra sure that groups are
equivalent at the outset
What are the two simple forms of within‐subjects designs?
.concurrent-measures design: An experiment
usi i hi ing awithin-groups d i i hi h design in which
participants are exposed to all the levels of an independent variable at roughly the same time, and a single attitudinal or behavioral preference is the dependent variable. (taste coke taste pepsi, choose favorite)
Repeated-measures designs: An experiment
with a within-groups design in which
participants respond to a dependent variable
more than once, after exposure to each level of
the independent variable.
Describe counterbalancing, and explain itsrole in the internal validity of a within‐subjects design.
.Counterbalancing: Presenting the levels of the
independent variable to participants in
different orders to control for order effects.
Interrogate the construct validity ofthemeasured variable in an experiment.
.ASK
How domanipulation checks provide evidence forthe construct validity of an experiment? Why does
theorymatter as you evaluate construct validity?
.ASK
Besides generalization to other participants, what other aspect of generalization is external validity
concerned with?
.ASK
Explain why experimenters usually prioritize internal validity over external validity when itis difficultto
achieve both.
.b/c without internal validity, your results are meaningless regardless of wethere or not your experiment is externally valid
Cohen’s D equivalents to r
d = strength = r .20 = weak/small = .10 .50 = moderate/medium = .30 .80 = strong/large = .50
Summarize the three threatsto internal validity thatthissection has covered.
design confounds, selection effects, order effects
Review three threatsto internal validity: design confounds,selection effects, and order effects. What
particular problems do these threats pose?
.
Whatis a one‐group, pretest/posttest design, and which threatsto internal validity are especially
applicable to this design?
.One-group, pretest/posttest design: A study in
which a researcher recruits one group of
pp p p articipants; measures them on a pretest; exposes
them to a treatment, intervention, or change; and
then measures them on a posttest.
Threats to internal validity that especially apply to
this design:
Maturation, history, regression, attrition, testing, and
instrumentation.
Indicate which ofthe threatsto internal validity would be relevant even to a two‐group, posttest‐only
design.
Observer bias, demand characteristics, placebo effect
Explain how comparison groups, double‐blind studies, and other design choices can help researchers
avoidmany ofthese threatsto internal validity.
Double-blind study: A study in which neither the
participants nor the researchers who evaluate
them know who is in the treatment group and
who is in the comparison group.
When a double-blind study is not possible a blind study is not possible, a
variation might be an acceptable alternative.
K i g b bli d t diti i Keeping observers blind to condition is even
more important when they are rating behaviors
th t diffi lt t d that are more difficult to code.
Articulate the reasonsthat a studymightresultin null effects: not enough variance between groups,too
much variance within groups, or a true null effect.
The independent variable really does not affect the dependent variable.
The study was not designed well enough.
Some obscuring factor in the study prevented the researchers from detecting the covariance
.Not enuf b/t groups variance: Weak manipulations, insensitive measures, and
reverse confounds might prevent an experiment
from detecting a true difference that exists
between 2 or more experimental groups.
Important to ask about construct validity:
Was the independent variable manipulation strong
enough to cause a difference between groups?
Was the dependent variable measure sensitive enough
to detect that difference?
Describe atleasttwo waysthat a studymightshow inadequate variance between groups, and indicate
how researchers can identify such problems.How can a studymaximize variability between
independent variable groups? (There are four ways.)
.Floor/Ceiling effects
.Noisy data
Weak manipulations, insensitive measures, and reverse confounds might prevent an experiment from detecting a true difference that exists between 2 or more experimental groups.
Important to ask about construct validity:
Was the independent variable manipulation strong
enough to cause a difference between groups?
Was the dependent variable measure sensitive enough
to detect that difference?
Explain why large within‐group variance can obscure a between‐group difference.
.TOO MUCH NOISE! measurement error?
Describe three causes of within‐group variance— measurement error, individual differences, and
situation noise.How can a studyminimize variability within groups? (There are three ways.)
.meas error: use reliable measurements, measure more instances
.indiv diff: change design, use either within-groups or matched-groups design
add more participants
.sit noise: control irrelevant events, sounds, distractions
In your own words, describe why Wansink’sstudy on price and package size was a factorial design.
.
Articulate how a crossed factorial design works.
.
Explain two reasonsto conduct a factorialstudy.
.
Review studies with one independent variable, which show a simple “difference.”Describe an
interaction as a “difference in differences.”
.
Describe interactionsin terms of “it depends.”
.
How can you detectmain effects and an interaction froma table ofmeans? Froma line graph? Froma
bar graph?
.
Describe how the same 2 × 2 designmight be conducted as a between‐subjectsfactorial, a within‐
subjectsfactorial, or amixed factorial design.
.
Indicate how the different designs change the number of participantsrequired: Which design requires
themost? Which requiresthe fewest?
.
Given a factorial notation (e.g., 2 × 2), identify the number ofindependent variables,the number of
levels of each variable,the number of cellsin the design, and the number ofmain effects and
interactionsthat will be relevant
.
Why is amain effect better called an “overall effect”?
.
Explain the basic logic ofthree‐way factorial designs.
.
How can you determine,froma graph, whether a study shows a three‐way interaction
.
Explain how quasi‐experiments can be either between‐subjects designs or within‐subjects designs.
.
Define the following quasi‐experimental designs: nonequivalent control group design, interrupted time‐
series design, and nonequivalent groupsinterrupted time‐series design.
.
How is a nonequivalent control groups design differentfroma true between‐subjects experiment?
.
How are interrupted time‐series designs and nonequivalent control groupsinterrupted time‐series
designs differentfromtrue within‐subjects experiments?
.
Explain whether quasi‐experimentalstudies avoid the following threatsto internal validity:selection,
maturation, history,regression, attrition,testing, instrumentation, observer bias, experimental demand,
and placebo effects.
.
Describe why both the design and the results of a study are importantfor assessing a quasi‐experiment’s
internal validity.
.
What are three reasonsthat a researchermight conduct a quasi‐experiment,ratherthan a true
experiment,to study a research question? Explain the trade‐offs(i.e.,sacrifices or disadvantages) of
using a quasi‐experimental design.
.
Interrogate quasi‐experimental designs by asking about construct validity, external validity, and
statistical validity.
.
