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Copyright © Allyn & Bacon (2007)Copyright © Allyn & Bacon (2007)

Correlational and Correlational and Differential ResearchDifferential Research

Graziano and RaulinGraziano and RaulinResearch Methods: Chapter 7Research Methods: Chapter 7This multimedia product and its contents are protected under copyright law. The following are This multimedia product and its contents are protected under copyright law. The following are prohibited by law: (1) Any public performance or display, including transmission of any image prohibited by law: (1) Any public performance or display, including transmission of any image over a network; (2) Preparation of any derivative work, including the extraction, in whole or in over a network; (2) Preparation of any derivative work, including the extraction, in whole or in part, of any images; (3) Any rental, lease, or lending of the program.part, of any images; (3) Any rental, lease, or lending of the program.


Correlational ResearchCorrelational Research

Quantifies the strength of the Quantifies the strength of the relationship between two or more relationship between two or more variablesvariables

Value of correlational researchValue of correlational research– Correlations can be used for predictionCorrelations can be used for prediction– Evidence consistent or inconsistent with a Evidence consistent or inconsistent with a

theorytheory Cannot prove a theory, but could negate a theoryCannot prove a theory, but could negate a theory

Note: Correlations Note: Correlations CANNOTCANNOT establish establish causationcausation


Correlation and Correlation and CausationCausation If A and B are If A and B are

correlated, then …correlated, then …– A could cause BA could cause B– B could cause AB could cause A– Another variable Another variable

could cause both A could cause both A and Band B

Must be cautious Must be cautious in drawing in drawing conclusionsconclusions


Differential Research Differential Research MethodsMethods Compare two or more preexisting groupsCompare two or more preexisting groups Similar to both correlational and Similar to both correlational and

experimental researchexperimental research– Same form as experimental researchSame form as experimental research– Conceptually similar to correlational research Conceptually similar to correlational research

(variables measured, but not manipulated)(variables measured, but not manipulated) Cross-sectional design in developmental Cross-sectional design in developmental

research is differential researchresearch is differential research


Cross-Sectional andCross-Sectional andLongitudinal ResearchLongitudinal Research Cross-sectional designs are fasterCross-sectional designs are faster

– Can test many age groups simultaneouslyCan test many age groups simultaneously But cohort effects can be a problemBut cohort effects can be a problem

– Defined as “shared life experiences of Defined as “shared life experiences of people of a given age that lead them to people of a given age that lead them to behave similarly to others their age and behave similarly to others their age and different from people of other ages”different from people of other ages”

Longitudinal designs are essentially Longitudinal designs are essentially time-series designstime-series designs


Artifacts andArtifacts andConfounding VariablesConfounding Variables Confounding occurs when two variables Confounding occurs when two variables

vary togethervary together– Need to have them vary independently, Need to have them vary independently,

usually by holding all but one variable usually by holding all but one variable constantconstant

– Failing to provide this control could result in Failing to provide this control could result in artifactual findingsartifactual findings

– Procedures standardized for this reasonProcedures standardized for this reason Comparing groups is reasonable Comparing groups is reasonable ONLY ONLY

IFIF we standardized the measurement we standardized the measurement proceduresprocedures


Correlational versus Correlational versus DifferentialDifferential Both involve the measurement, but Both involve the measurement, but

not manipulation, of variablesnot manipulation, of variables– Therefore, neither is able to establish Therefore, neither is able to establish

causationcausation Differential is higher constraint Differential is higher constraint

because because – The researcher can select the comparison The researcher can select the comparison

group(s) to control at least some of the group(s) to control at least some of the potential confounding variables, thus potential confounding variables, thus providing stronger evidence for a theoryproviding stronger evidence for a theory


When to Use Each When to Use Each MethodMethod Correlational MethodCorrelational Method

– When we are interested in knowing the When we are interested in knowing the strength of a relationship for predictive strength of a relationship for predictive purposespurposes

– Often included to help interpret the primary Often included to help interpret the primary findings of a studyfindings of a study

Differential ResearchDifferential Research– When the manipulation of an independent When the manipulation of an independent

variable is impractical, impossible, or unethicalvariable is impractical, impossible, or unethical– Then we rely on comparing preexisting groupsThen we rely on comparing preexisting groups


Doing Correlational Doing Correlational ResearchResearch Steps in conducting correlational Steps in conducting correlational

researchresearch– Developing the problem statementDeveloping the problem statement– Measuring the VariablesMeasuring the Variables– Obtaining the SampleObtaining the Sample– Analyzing the DataAnalyzing the Data– Interpreting the ResultsInterpreting the Results

Correlational research is often Correlational research is often embedded in larger studiesembedded in larger studies


Developing a Problem Developing a Problem StatementStatement ““What is the relationship between What is the relationship between

variable X and variable Y?”variable X and variable Y?” Often want to correlate available Often want to correlate available

demographic variables with the demographic variables with the dependent measures or intercorrelate dependent measures or intercorrelate the dependent measures in higher-the dependent measures in higher-constraint researchconstraint research– Useful in detecting confounding variablesUseful in detecting confounding variables– Provides hypotheses for later researchProvides hypotheses for later research


Measuring the Measuring the VariablesVariables Need to use reliable and valid Need to use reliable and valid

measuresmeasures Need to controlNeed to control

– Experimenter expectancyExperimenter expectancy Researchers tending to see what they expect to seeResearchers tending to see what they expect to see

– Experimenter reactivityExperimenter reactivity Researchers unconsciously influencing participantsResearchers unconsciously influencing participants

– Measurement reactivityMeasurement reactivity Participants responding differently because they Participants responding differently because they

know they are being observedknow they are being observed


Controlling these Controlling these effectseffects Experimenter expectancyExperimenter expectancy

– Use objective measures whenever possibleUse objective measures whenever possible Experimenter reactivityExperimenter reactivity

– Minimize experimenter contact Minimize experimenter contact Measurement reactivityMeasurement reactivity

– Use filler items to distract participantsUse filler items to distract participants– Use unobtrusive measures when possibleUse unobtrusive measures when possible– Separate the measurements in timeSeparate the measurements in time


Sampling Sampling ConsiderationsConsiderations Want the sample to be representativeWant the sample to be representative Is the observed relationship the same Is the observed relationship the same

in each subpopulation?in each subpopulation?– If we suspect such differences, we should compute If we suspect such differences, we should compute

the correlation in each subpopulationthe correlation in each subpopulation– Moderator VariableModerator Variable: a variable that seems to : a variable that seems to

modify the relationship between other variablesmodify the relationship between other variables e.g., sex: males and females showing different e.g., sex: males and females showing different

patterns of relationship between variablespatterns of relationship between variables


Analyzing the DataAnalyzing the Data

Correlations range from -1.00 to +1.00Correlations range from -1.00 to +1.00– Size indicates strength of the relationshipSize indicates strength of the relationship– Sign indicates direction of the relationshipSign indicates direction of the relationship

Many types of correlationsMany types of correlations– Pearson product-moment correlationPearson product-moment correlation– Spearman rank-order correlationSpearman rank-order correlation– Advanced techniques (multiple correlation, Advanced techniques (multiple correlation,

canonical correlation, partial correlation, canonical correlation, partial correlation, path analysis)path analysis)


Interpreting the DataInterpreting the Data

Note size and sign of correlationNote size and sign of correlation– Indicates strength and direction of Indicates strength and direction of

relationshiprelationship Is the correlation significantly different Is the correlation significantly different

from zero (i.e., evidence for a from zero (i.e., evidence for a relationship)?relationship)?– Is the Is the pp value < alpha? value < alpha?

Coefficient of DeterminationCoefficient of Determination– rr22 indicates the proportion of variance indicates the proportion of variance

accounted foraccounted for


Doing Differential Doing Differential ResearchResearch Developing the problem statementDeveloping the problem statement Measuring the variablesMeasuring the variables Selecting appropriate control Selecting appropriate control

groupsgroups Obtaining the sampleObtaining the sample Analyzing the dataAnalyzing the data Interpreting the resultsInterpreting the results


Developing a Problem Developing a Problem StatementStatement ““Does Group A differ from Group B?”Does Group A differ from Group B?” Developing good problem statementsDeveloping good problem statements

– Select theoretically interesting groups to Select theoretically interesting groups to compare compare

– Compare them on theoretically interesting Compare them on theoretically interesting variablesvariables

– Best to compare groups that differ on only Best to compare groups that differ on only a single variable if possiblea single variable if possible

– Several comparisons are bestSeveral comparisons are best


Measuring the Measuring the VariablesVariables Dependent variable is usually continuous, Dependent variable is usually continuous,

but could be categoricalbut could be categorical Independent variable is categorical or is a Independent variable is categorical or is a

continuous variable converted to continuous variable converted to categoriescategories– Unlike experimental research, the independent Unlike experimental research, the independent

variable is measured, rather than manipulatedvariable is measured, rather than manipulated Need operational definitions for Need operational definitions for

– Dependent VariableDependent Variable– Independent variablesIndependent variables


Selecting Control Selecting Control GroupsGroups Select control groups to avoid Select control groups to avoid

confoundingconfounding– A variable can confound results A variable can confound results only ifonly if

a) it affects the scores on the dependent variablea) it affects the scores on the dependent variableb) the groups differ on this variableb) the groups differ on this variable

Ideal control group is identical to Ideal control group is identical to experimental group on all variables experimental group on all variables except the variable that defines the except the variable that defines the groupsgroups– Rarely possible, so multiple comparisons Rarely possible, so multiple comparisons

groups are typicalgroups are typical


Sampling of Sampling of ParticipantsParticipants Like all research, we want representative Like all research, we want representative

sampling to permit generalizationsampling to permit generalization Many factors can bias samplingMany factors can bias sampling

– Where we have access to participantsWhere we have access to participants– How we go about identifying participantsHow we go about identifying participants– Even factors like time of day that we sampleEven factors like time of day that we sample

Participants who drop out of the study Participants who drop out of the study can limit generalizabilitycan limit generalizability


Analyzing the DataAnalyzing the Data

Same procedures as those used Same procedures as those used to analyze experimental researchto analyze experimental research

Type of analysis depends on the Type of analysis depends on the number of groups and the level of number of groups and the level of measurement measurement – Score data: Score data: tt-test or ANOVA-test or ANOVA– Ordinal data: Mann-Whitney Ordinal data: Mann-Whitney UU-test-test– Nominal data: Chi squareNominal data: Chi square


Interpreting the Interpreting the ResultsResults Reject null hypothesis (of no group Reject null hypothesis (of no group

difference) if the difference) if the pp < alpha < alpha Difficult to draw a strong conclusion Difficult to draw a strong conclusion

from differential researchfrom differential research– Sampling considerationsSampling considerations– Unlikely that all potential confounding Unlikely that all potential confounding

variables will have been adequately variables will have been adequately controlledcontrolled


Blanchard et al. (2001)Blanchard et al. (2001)

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Limitations of these Limitations of these MethodsMethods Problems in determining causationProblems in determining causation

– A correlation does not imply causalityA correlation does not imply causality If If AA and and B B are correlated, thenare correlated, then

– AA could cause could cause BB– BB could cause could cause AA– Some other variable could cause bothSome other variable could cause both

Confounding variablesConfounding variables– Without experimental control, it is virtually Without experimental control, it is virtually

impossible to avoid confounding variablesimpossible to avoid confounding variables


SummarySummary

Both correlational and differential Both correlational and differential research involve measuring the research involve measuring the relationship between variablesrelationship between variables

Drawing causal inferences is riskyDrawing causal inferences is risky Selecting appropriate control Selecting appropriate control

groups in the differential research groups in the differential research design can control some, but design can control some, but typically not all, potential typically not all, potential confounding variablesconfounding variables

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