Which of the following questions is necessary to ask when interrogating statistical validity?

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 ofthestatistical 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, TvViolence2011AND, 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.

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.

1. Even though multivariate designs analyzed with regression statistics can control for third variables they cannot establish temporal variables, they cannot establish temporal precedence.2. 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 forpotential 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 VARIABLEKenny (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 awayORtest 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 forMULTIVARIATE 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 preexistingdifferences 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.

How domanipulation checks provide evidence forthe construct validity of an experiment? Why does
theorymatter as you evaluate construct validity?

Besides generalization to other participants, what other aspect of generalization is external validity
concerned with?

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 evenmore 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 indicatehow researchers can identify such problems.How can a studymaximize variability between

independent variable groups? (There are four ways.)

.Floor/Ceiling effects.Noisy dataWeak 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 designadd 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 oflevels 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 trueexperiment,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.

Explain three differences between small‐Nand large‐Nexperiments.

Describe three small‐Ndesigns(stable‐baseline designs,multiple‐baseline designs, and reversal designs)
and explain how each design addressesinternal validity.

Give examples of questions you would ask about a small‐Ndesign to interrogate allfour big validities

Explain the trade‐offs of using a small‐Ndesign.

How do inferentialstatistics help researchers estimate whethertheirstudies are replicable?

Describe how the three types ofreplication studies are similar and different.

Compare the value of a single study to that of a body ofresearch, or a literature.

In your own words, describe the steps a researcherfollowsin ameta‐analysis. What can ameta‐analysis
tell us?

Explain what ameta‐ analysis hasin common with direct and conceptualreplication.

Give examples of how external validity applies both to other participants and to othersettings

In your own words, describe the difference between generalizationmode and theory‐testingmode.

Which ofthe three types of claims(frequency, association, or causal)is almost always conducted in
generalizationmode? Which ofthe three claims are usually conducted in theory‐ testingmode?

Explain why researchers who are operating in theory‐ testingmodemight not attemptto use a randomsample in theirresearch. What validity are they prioritizing? What aspects oftheirresearch are they

emphasizing (for now)?

Summarize the goal of cultural psychology. What doesthisfield suggest about working in theory‐ testing
and generalizationmodes?

Reevaluate two common assumptionsfromthe perspectives of generalizationmode and theory‐testingmode:thatimportantstudies use diverse,randomsamples and thatimportantstudiestake place in real‐ 

world settings.

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?

In one ortwo briefsentences, explain how you would interrogate the construct validity of a bivariate
correlation.

What are five questions you can ask aboutthe statistical validity of a bivariate correlation?Do all ofthestatistical validity questions apply the same way when bivariate correlations are represented as bar

graphs?

Which ofthe three rules of causation is almost alwaysmet by a bivariate correlation? Which two rules
might not bemet by a correlationalstudy?

Give examples ofsome questions you can ask to evaluate the external validity of a correlationalstudy.

Why can’t a simple bivariate correlationalstudymeet allthree rulesfor establishing causation?

Explain how longitudinal designs are conducted. Why is a longitudinal design called amultivariate
design?

Identify the three types of correlationsin a longitudinal correlational design: cross‐ sectional
correlations, autocorrelations, and cross‐lag correlations.

Interpret different possible outcomesin cross‐lag correlations, andmake a causal inference fromeach
pattern.

Explain howmultiple‐regression designs are conducted.Describe in your own words whatitmeansto
say thatsome variable “was controlled for” in amultivariate study.

Define dependent variables and predictor variablesin the context ofmultiple‐regression data.How
many dependent variables are there in amultiple‐regression analysis?Howmany predictor variables?

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?

Give atleastthree phrasesthatindicate that a study used amultiple regression analysis.

What are two reasonsthatmultiple regression designs cannot completely establish causation? Explain
why experiments are superiortomultiple‐regression designsfor controlling forthird variables.

Explain the value of pattern and parsimony in research.

Consider why journalistsmight preferto reportsingle studies,ratherthan parsimonious patterns of
data. What problemsresultsfromthistendency?

Identify amediation hypothesis and sketch a diagramofthe hypothesized relationship.Describe the
stepsfortesting amediation hypothesis.

Articulate the difference betweenmediators,third variables, andmoderating variables.

Give an example of a question you would ask to interrogate each ofthe four validitiesfor amultivariate
study.

Distinguishmeasured frommanipulated variablesin a study.

What are theminimumrequirementsfor a study to be an experiment?

In your own words, define the termsindependent variable, dependent variable, and control variable.

How do experimentssatisfy the three causalrules?

How are design confounds and control variablesrelated?

Describe randomassignment and explain itsrole in establishing internal validity.

Describematching, explain itsrole in establishing internal validity, and explain situationsin which
matchingmay be preferred to randomassignment.

Describe how the proceduresfor between‐subjects and within‐subjects experiments are different.
Explain the pros and cons of each type of design.

Describe how posttest‐only and pretest/posttest designs are both between‐subjects designs. Explain
how they differ, and when a researchermay use each one.

What are the two simple forms of within‐subjects designs?

Describe counterbalancing, and explain itsrole in the internal validity of a within‐subjects design.In your own words,summarize all ofthe advantages and disadvantages of within‐subjects designs(hint:
there are 3 of each).

Interrogate the construct validity ofthemeasured variable in an experiment.

How domanipulation checks provide evidence forthe construct validity of an experiment? Why does
theorymatter as you evaluate construct validity?

Besides generalization to other participants, what other aspect of generalization is external validity
concerned with?

Explain why experimenters usually prioritize internal validity over external validity when itis difficultto
achieve both.

What doesitmean when an effectsize islarge (as opposed to small)in an experiment?

Summarize the three threatsto internal validity thatthissection has covered.

Review three threatsto internal validity: design confounds,selection effects, and order effects. What
particular problems do these threats pose?

Describe the following nine threatsto internal validity: history,maturation,regression, attrition,testing,instrumentation, observer bias, demand characteristics, and placebo 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?

Indicate which ofthe threatsto internal validity would be relevant even to a two‐group, posttest‐only
design.

Explain how comparison groups, double‐blind studies, and other design choices can help researchers
avoidmany ofthese threatsto internal validity.

Articulate the reasonsthat a studymightresultin null effects: not enough variance between groups,too
much variance within groups, or a true null effect.

Describe atleasttwo waysthat a studymightshow inadequate variance between groups, and indicatehow researchers can identify such problems.How can a studymaximize variability between

independent variable groups? (There are four ways.)

Explain why large within‐group variance can obscure a between‐group difference.

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.)

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 oflevels 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 trueexperiment,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.

Explain three differences between small‐Nand large‐Nexperiments.

Describe three small‐Ndesigns(stable‐baseline designs,multiple‐baseline designs, and reversal designs)
and explain how each design addressesinternal validity.

Give examples of questions you would ask about a small‐Ndesign to interrogate allfour big validities

Explain the trade‐offs of using a small‐Ndesign.

How do inferentialstatistics help researchers estimate whethertheirstudies are replicable?

Describe how the three types ofreplication studies are similar and different.

Compare the value of a single study to that of a body ofresearch, or a literature.

In your own words, describe the steps a researcherfollowsin ameta‐analysis. What can ameta‐analysis
tell us?

Explain what ameta‐ analysis hasin common with direct and conceptualreplication.

Give examples of how external validity applies both to other participants and to othersettings

In your own words, describe the difference between generalizationmode and theory‐testingmode.

Which ofthe three types of claims(frequency, association, or causal)is almost always conducted in
generalizationmode? Which ofthe three claims are usually conducted in theory‐ testingmode?

Explain why researchers who are operating in theory‐ testingmodemight not attemptto use a randomsample in theirresearch. What validity are they prioritizing? What aspects oftheirresearch are they

emphasizing (for now)?

Summarize the goal of cultural psychology. What doesthisfield suggest about working in theory‐ testing
and generalizationmodes?

Reevaluate two common assumptionsfromthe perspectives of generalizationmode and theory‐testingmode:thatimportantstudies use diverse,randomsamples and thatimportantstudiestake place in real‐ 

world settings.

+/- .10 = small or weak+/- .30 = Medium, or moderate

+/- .50 = Large, or strong

Point-biserial correlation

A statistical test used for evaluating the association between one categorical variable and one quantitative

variable.

A statistical test designed to evaluate the association between two

categorical variables

describe random assignment and its role in establishing internal validity

With random assig , yp g nment, any preexistingdifferences between participants should be distributed evenly across both groups, and their

effect canceled out.

In your own words,summarize all ofthe advantages and disadvantages of within‐subjects designs(hint:
there are 3 of each).

.disadv:1. The potential for order effects.2. Demand characteristics: Cues that lead participants to guess a study participants to guess a study s hypotheses or 's hypotheses or goals.3. A within-groups design might be impossible..adv:1. Need less participants2. Easier to find a significant effect (greater power).3. ensures participant in each treatment group is equivalentThe principal advantage of a within-groups design is that it ensures that the participants in the two treatment groups will be equivalent

POWER, easier to detect stat sig restults