《研究方法》研究生教学课件

MBMZ01ResearchMethodologyIntroductionMaterialsadoptedfromourtextbookandweremainlydevelopedbyProf.P.C.ChangSomevocabularyexplanationsareobtainedfromResearchFrameworkResearchIdea(Interesting

NewInsights;Importance)MotivationProblemStatementTheoreticalFrameworkMotivatingLiteratureResearchMethodSampleSelectionValidityandReliabilityIssuesAnalysisImplicationsConclusionConsiderthesecoursesofactionAnelementaryschoolprincipalestablishedasetofdifficultteachergoalstoimprovestudents’academicperformance.Acompanypresidentjoinsanalliancewithotherfirmsintheindustrytoimprovereturnsfromresearchanddevelopmentexpenditures.Abasketballcoachhasteammemberstakedancinglessonstoimproveagility.Ahumanresourcemanagerproposesaflexiblebenefitplantoreduceemployeeturnover.CausalRelationshipsCausalrelationship---onefactorinfluencesanother.Expectedrelationships---expectationsmayormaynotholdEmpiricalResearchEmpiricalresearchcanhelpobtainevidenceontheveracity

ofexpectedcausalrelationshipsofthetypedescribedhere.EmpiricalresearchSystematicstudyofrelationshipsbetweenscoresobtainedfromcasesonmeasures.Veracity:correctnessoraccuracy,asofthesensesorofascientificinstrumentEmpiricalResearchCasesEntities(e.g.,individuals,groups,organizations)investigatedinresearch.MeasuresInstrumentsusedtoobtainscoresfromparticipants.Scores(data)Numericalinformationaboutcasesobtainedonmeasures.ResearchActivitiesEmpiricalresearchinvolvesthreeactivitiesMeasurementDesignAnalysisResearchActivitiesMeasurementActivitiesassociatedwithmeasuringcases.ResearchDesignOverallplanofastudy–Establishesprocedurestoobtaincasesforstudyandtodeterminehowscoresareobtainedonmeasuresofcases.AnalysesUsedtodescribescoresonsinglemeasuresandtoidentifyrelationshipsthatmayexistbetweenscoresacrossdifferentmeasuresQuantitativestudiesinvolvetheuseofstatistics.ResearchActivitiesThelineslinkingthethreeresearchactivitiessignaltwothings.Theysignalthattheseresearchactivitiesarerelatedinpractice.Theysignalthatknowledgeofanyoneresearchactivityishelpfulinlearningabouttheotheractivities.Notallresearchisempirical.Notallempiricalresearchisquantitative.QualitativevsQuantitativeResearchQualitativeresearch?Quantitativeresearch?ResearchMethodsResearchmethodshavetwoadvantagesforobtainingknowledge.Researchmethodsproperlyconductedaddressquestionssystematically.Researchproperlyperformedisapublicprocess;itistransparent.TermstoknowCausalrelationshipEmpiricalresearchScores(data)CasesMeasuresMeasurementResearchdesignAnalysesQuantitativeresearchQualitativeresearchHomeworkWhatarethesimilaritiesandmajordifferencesbetweenqualitativeandquantitativeresearchstudies?MBMZ01ResearchMethodologyChapter2AModelofEmpiricalResearchChapterOutlineResearchVariablesConceptualandOperationalVariablesDependentandIndependentVariablesTheModelConceptualRelationshipsOperationalRelationshipsConceptualtooperationalRelationshipsGeneralizingfromtheModelStatisticalGeneralizationExternalGeneralization

AmodelofempiricalresearchAmodelofempiricalresearchexplicatescausalrelationshipsThemodelcontributestocausalunderstanding.Themodelhelpyouunderstandresearchers’framesofreferencewhenyoureadresearchreports.Themodelprovidesagoodwaytothinkaboutissuesasyouconductandevaluateyourownresearch.ResearchVariablesVariablesCharacteristicsofobjectsoreventsthatcantakeontwoormorevalues.(textbook)Avariableisanyentitythatcantakeondifferentvalues(Researchmethod-knowledgebase)Example?Age(1,2….)Gender(male/female/other)ConceptualandOperationalVariablesCausalrelationshipataconceptuallevel“Iknowthateducationleadstofinancialsuccess.”expressesabeliefaboutacausalrelationshipataconceptuallevel.Conceptualvariables

(Constructs)

Mentaldefinitionsofobjectsoreventsthatcanvary.Example,Iknowthateducationleadstofinancialsuccess.Theconstruct

education

maybedefinedastheknowledgeandproblem-solvingabilitiesoneacquiresfromformallearningenvironments.ConceptualandOperationalVariablesEmpiricalresearchactivitiesarecarriedoutatanoperationallevelofabstraction.Empiricalresearchobtainsscoresfromcasesonmeasures.Operationalvariables:Variableswithameasuretoobtainscoresfromcases.Example,Thenumberofyearstherespondentshaveattendedschoolisanoperationalmeasureofeducation.ConceptualandOperationalVariablesDependentandIndependentVariablesDependentvariables(DV)ResearchoutcomeTheconsequenceinacausalrelationshipVariablesthatresearchersseektounderstand,explain,and/orpredict.Independentvariables(IV)ToinfluenceorpredictdependentvariablesHelpsexplainorpredictadependentvariableAcauseinacausalrelationship.Whydosomeathleticteamssucceedmorethanothers?Variablescanbedependentinonecontextandindependentinanother.IVrepresentsacauseDVrepresentstheconsequence.IVsmaysimplypredictDVswithoutcausallinkages.DependentandIndependentVariablesTheModel’’IVandDVareidentifiedbyXandY,respectively’isusedtodesignatethatavariableisspecifiedattheconceptuallevelRepresentthedirectionofinfluenceorcauseThedistinctionbetweenconceptualandoperationalvariablesisrepresentedverticallyThedistinctionbetweenindependentanddependentvariablesisrepresentedhorizontally.DependentandIndependentVariablesConceptualRelationshipsThetophorizontalline(a)representsacausalconceptualrelationship.CausalconceptualrelationshipAsituationinwhichanindependentconstructisthoughttoinfluenceadependentconstruct.HypothesesTentativebeliefsaboutrelationshipsbetweenvariables.ValidityInresearch,whenaconclusionorinferenceistrue.ReferstothetruthofthecausalconceptualrelationshipbetweenXandY.ConceptualRelationshipsEmpiricalRelationshipsAnEmpiricalRelationship,representedbyline(d),referstothecorrespondencebetweenscoresonmeasuresXandY.Line(d)is

solidtosignalthatthisrelationshipcanactuallybeobserved,typicallybyusingsomestatisticalprocedures.InternalValidityLine(c)signalsacausalrelationshipbetweenXandY.InternalvalidityPresentwhenvariationinscoresonameasureofanIVisresponsibleforvariationinscoresonameasureofaDV.InternalvalidationMethodsusedtodeterminewhetherinternalvalidityislikely.

Internalcausalcriteria:

1.Independentanddependentvariablesaremeaningfullyrelated.2.Variationintheindependentvariableiscontemporaneouswith,orprecedes,variationinthedependentvariable.3.Thereisareasonablecausalexplanationfortheobservedrelationshipandtherearenoplausiblealternativeexplanationsforit.InternalStatisticalValidityInternalstatisticalvalidityPresentwhenanempiricalrelationshipisnotduetochance.StatisticalvalidationTheuseofprobabilitytheorytoassessinternalstatisticalvalidity.ConceptualtoOperationalRelationshipsConstructvalidityPresentwhenthereisahighcorrespondencebetweenthescoresobtainedonameasureandthementaldefinitionoftheconstructitisdesignedtorepresent.(Lineb1andb2)ConstructvalidationMethodsusedtoestimateameasure’sconstructvalidity.GeneralizingfromtheModelStatisticalgeneralizationvalidityPresentwhenanempiricalrelationshipobservedonasampleofcasesprovidesacorrectestimateoftherelationshipinthepopulationofcasesfromwhichthesamplewasdrawn.Aninferenceismadefromanempiricalrelationshipobservedonasample(d)tothecorresponding,butunknown,empiricalrelationship(D)inthepopulation.ExternalgeneralizationPresentwhenfindingsobtainedinaresearchstudy,otherthanstatisticalgeneralization,arecorrectlygeneralized.ExternalvalidationInvestigateallothertypesofresearchgeneralization.ExternalvalidityPresentwhengeneralizationsoffindingsobtainedinaresearchstudy,otherthanstatisticalgeneralization,aremadeappropriately.Meta-analysisAresearchproceduresdesignedtoprovidequantitativeestimatesofthegeneralizabilityofrelationshipsacrossstudies.GeneralizingfromtheModelTermstoknowVariablesConceptualvariableOperationalvariableDependentvariableIndependentvariableCausalconceptualrelationshipHypothesisValidityVerisimilitudeEmpiricalrelationshipInternalvalidityInternalvalidationInternalstatisticalvalidityStatisticalvalidationTheoryConstructvalidityConstructvalidationStatisticalgeneralizationvalidityExternalvalidityExternalvalidationMeta-analysisMBMZ01ResearchMethodologyChapter3MeasurementFoundations:ValidityandValidationConstructDefinitionsConstructvalidityreferstothedegreetowhichinferencescanlegitimatelybemadefromtheoperationalizationsinyourstudytothetheoreticalconstructsonwhichthoseoperationalizationswerebased.(Source:KnowledgeBase)Thereisnodirectwaytomeasureconstructs,becausetheyareconceptualphenomena.Asaconsequence,thereisnodirectwaytoassessconstructvalidity.Itmustbeinferredfromavarietyofcriteria.Theseinferencesaremadebyexaminingscoresonmeasuresandcomparingthemwiththeoreticalpropositionsabouthowthescoresshouldperform.Constructvalidmeasurementresultsinaclosecorrespondencebetweentheconstructofinterestandthescoresprovidedbythemeasures.Themostusefulconceptualdefinitionshavetwoelements:ConstructdomainNomologicalnetworkConstructDefinitionsIdentifiesthenatureoftheconstructbyspecifyingitsmeaning.ExplainswhataresearcherhasinmindfortheconstructContainsadictionary-likestatementthatdescribestheconstructdomain.Speakstowhatisincludedintheconstruct.ConstructDomainNomologicalNetworkSpecifieshowvaluesoftheconstructshoulddifferacrosscasesandcondition.Relationshipsbetweenaconstructundermeasurementconsiderationandotherconstructs./kb/nomonet.phpThisnetworkwouldincludethetheoreticalframeworkforwhatyouaretryingtomeasure,anempiricalframeworkforhowyouaregoingtomeasureit,andspecificationofthelinkagesamongandbetweenthesetwoframeworks.ConstructDefinitionIllustrationPersonalcomputersatisfactionisanemotionalresponseresultingfromanevaluationofthespeed,durability,andinitialprice,butnottheappearanceofapersonalcomputer.Thisevaluationisexpectedtodependonvariationintheactualcharacteristicsofthecomputer(e.g.speed)andontheexpectationsaparticipanthasaboutthosecharacteristics.Whencharacteristicsmeetorexceedexpectations,theevaluationisexpectedtobepositive(satisfaction).Whencharacteristicsdonotcometoexpectations,theevaluationisexpectedtobenegative(dissatisfaction).Peoplewithmoreeducationwillhavehigherexpectationsandhencelowercomputersatisfactionthanthosewithlesseducation.ConstructDefinitionIllustrationComputersatisfactionasdefinedreferstospeed,durability,andprice.ItalsoexpectedthatsatisfactionwithappearanceisNOTpartofthedefinition.HypotheticalcomputersatisfactionquestionnaireMysatisfactionwith:VeryDissatisfiedDissatisfiedNeitherSatisfiednorDissatisfiedSatisfiedVerySatisfied1.Initialpriceofthecomputer123452.WhatIpaidforthecomputer123453.Howquicklythecomputerperformscalculations123454.Howfastthecomputerrunsprograms123455.Helpfulnessofthesalesperson123456.HowIwastreatedwhenIboughtthecomputer12345MultidimensionalConstructsOne-dimensionalconstructsE.g.ComputersatisfactionMultidimensionalconstructsSatisfactionwithcomputerspeedSatisfactionwithcomputerdurabilitySatisfactionwithcomputerpriceLecture2

ConceptualtoOperationalRelationshipsConstructvalidityPresentwhenthereisahighcorrespondencebetweenthescoresobtainedonameasureandthementaldefinitionoftheconstructitisdesignedtorepresent.(Lineb1andb2)ConstructvalidationMethodsusedtoestimateameasure’sconstructvalidity.ConstructValidityChallengesTwomajorchallengesconfrontconstructvalidity.RandomerrorsCompletelyunsystematicvariationinscoresSystematicerrorsInmeasurement,whenscoresfromameasureconsistentlyvaryfromconstructvaliditybecauseofcontaminationand/ordeficiency.RandomErrorsTakinganaverageofseveralitemsdesignedtomeasurethesamethingisonewaytoaddressrandomerrors.Randomerrorstendto“average-out”acrossmultipleitems.Themoreitems,themoresuccessfullythistypeofrandomerroriscontrolled.SystematicErrorsContaminationInmeasurement,theportionofscoresthatmeasuressomethingotherthanthedefinedconstruct.(多測)DeficiencyInmeasurement,theportionofthedefinedconstructthatisnotcapturedbyscoresonameasureoftheconstruct.(少測)Items1and2relatetosatisfactionwithprice.Items3and4relatedtosatisfactionwithspeed.Items5and6askaboutsatisfactionwiththepurchasingexperience.(contamination)Themeasureisdeficientbecausetherearenoitemscapturingsatisfactionwithcomputerdurability.Mysatisfactionwith:VeryDissatisfiedDissatisfiedNeitherSatisfiednorDissatisfiedSatisfiedVerySatisfied1.Initialpriceofthecomputer123452.WhatIpaidforthecomputer123453.Howquicklythecomputerperformscalculations123454.Howfastthecomputerrunsprograms123455.Helpfulnessofthesalesperson123456.HowIwastreatedwhenIboughtthecomputer12345ConstructValidationContentValidityReliabilityConvergentValidityDiscriminantValidityCriterion-RelatedValidityInvestigatingNomologicalNetworksContentValidityAmeasureiscontentvalidwhenitsitemsarejudgedtoaccuratelyreflectthedomainoftheconstructasdefinedconceptually.Contentvalidationordinarilyhasexpertsinthesubjectmatterofinterestprovideassessmentsofcontentvalidity.Contamination?Deficiency?Itemsmeasuringcrossoverbetweenworkplaceandnon-workplaceactivities4我會在工作時間內以即時通訊處理私人或社交事務。123455我會在工作時間內以即時通訊處理與工作有關的事務。123456我會在工作時間內回覆與私人或社交有關的即時通訊。123457我會在工作時間內回覆與工作有關的即時通訊。123458在一天當中，我控制著是否將工作與社交活動結合在一起。12345ReliabilityReferstothesystematicorconsistentvarianceofameasure.Proportionofobservedscorevariability(circleonthefarright)thatisoverlappedbythemiddlecircle(systematic)representingtruescorevariability.TypesofReliabilityInternalconsistencyreliabilityThesimilarityofitemscoresobtainedonameasurethathasmultipleitems.Itcanbeassessedwhenitemsareintendedtomeasureasingleconstruct.Inter-raterreliabilityThedegreetowhichagroupofobserversorratersprovideconsistentevaluation.StabilityreliabilityTheconsistencyofmeasurementresultacrosstime.ReliabilityandConstructValidityReliabilityspeaksonlytoameasure’sfreedomfromrandomerrors.Itdoesnotaddresssystematicerrorsinvolvingcontaminationordeficiency.Reliabilityisnecessaryforconstructvaliditybutnotsufficient.Itisnecessarybecauseunreliablevariancemustbeconstructinvalid.Itisnotsufficientbecausesystematicvariancemaybecontaminatedandbecausereliabilitysimplydoesnotaccountfordeficiency.Reliabilityaddressesonlywhetherscoresareconsistent;itdoesnotaddresswhetherscorescaptureaparticularconstructasdefinedconceptually./stat_tool/reliabilityvalidity.htmConvergentValidityIspresentwhenthereisahighcorrespondencebetweenscoresfromtwodifferentmeasuresofthesameconstruct.Theareacrossedwithverticallinesshowstheproportionofvarianceinscoresfromthetwomeasuresthatisconvergent.Theareacrosseswithhorizontallinesshowscommonconstructvalidvariance.Theareacoveredonlybyverticallinesshowswherethetwomeasuressharevariancethatrepresentscontaminationfromaconstructvalidityperspective.Convergentvalidityalsodoesnotaddresswhethermeasuresaredeficient.DiscriminantValidityispresentwhenmeasuresofconstructsthataresupposedtobeindependentarefoundtohavealowcorrespondence.ExampleIfscoresontheresearcher’smeasureofcomputersatisfactionshowlittleornorelationshipwithscoresfromameasureofsatisfactionwithcomputerappearance,thendiscriminantvalidityevidenceisobtained.ConvergentValidityand

DiscriminantValidity收斂效度

指一份測驗分數要能夠和其他測量相同理論建構或潛在特質的測驗分數間具有高相關

區別效度

指一份測驗分數要能夠和其他測量不同理論建構或潛在特質的測驗分數間具有低相關

Criterion-RelatedValidityIspresentwhenscoresonameasurearerelatedtoscoresonanothermeasurethatbetterreflectstheconstructofinterest.NomologicalNetworksThericherthenetworkandthemoresupport,thegreateraresearcher’sconfidencethatthemeasureiscapturingvariancethatinconstructvalid.Informationobtainedintheconstructvalidationprocessalsomayleadtomodificationoftheconstruct.Forexample,incontrasttotheinitialdefinition,theresearchermayconsistentlyfindthatcomputerappearanceisrelatedtoameasureofcomputersatisfaction.Ifso,thedefinitionoftheconstructmaybechangedtoincludeappearancegiventhisempiricalinformation.NomologicalNetworksTermstoknowNomologicalnetworkRandomerrorsTruescoresSystematicerrorsContaminationDeficiencyContentvalidityFacevalidityReliabilityInternalconsistencyInter-raterreliabilityStabilityreliabilityConvergentvalidityDiscriminantvalidityCriterion-relatedvalidityOne-dimensionalconstructsMultidimensionalconstructsMBMZ01ResearchMethodologyChapter4MeasurementApplications:ResearchQuestionnairesDataCollectionTools

(MeasuringInstrument)DataCollectionMethodshttp:///piercech/ResearchMethods/Data%20collection%20methods/DATA%20COLLECTION%20METHODS.htmKnowledge-base/kb/measure.phpWikipediahttp:///wiki/Survey_data_collectionQuestionnaireQuestionnairesMeasuringinstrumentsthataskindividualstorespondtoasetofquestionsinverbalorwrittenform.Self-reportquestionnairesQuestionnairesthataskrespondentstoprovideinformationaboutthemselves.Informationobtainedinself-reportquestionnairesincludebiographicalinformation,attitudes,opinions,andknowledge.QuestionnairesIndividualsmaycompleteself–reportquestionnairesbyrespondingtowrittenquestionsortoquestionsshownonacomputerterminal.Self-reportsalsomaybeobtainedthroughaninterview.Respondbias/wiki/Response_biasQuestionnaireDecisionsQuestionstoPonderTwoquestionstoaddressbeforethedevelopmentShouldinformationbeobtainedwithawrittenquestionnaireoraninterview?Ifthequestionnaireisdesignedtoobtaininformationaboutindividuals,shouldthequestionnaireobtainitfromoutsideobserversorformindividualsreportingonthemselves?AlternativestoQuestionnaireConstructionIfthedatayouareinterestedinstudyingmayalreadybeavailable.

SecondaryDataIfameasureisavailablethatwillserveyourresearchinterest.QuestionnairesDevelopedbyOthersSecondaryDataInformationusedforresearchpurposesbutthathasbeencollectedforotherpurposes.Advantages:SavecostandtimeifavailableandapplicableConstructvalidity?QuestionnairesDevelopedbyOthersHowtogetasuitablequestionnairesdevelopedbyothers?Examineresearchreportsontopicsrelatedtoyourresearchinterests.Questionnaireshasbeenprovedthattheyhaveagoodconstructvalidity.

QuestionnaireTypeSelf-ReportsVersusObservationsExample:EmployeeperformanceConstructsthataddressinternalmentalstatesofindividualsoftencanbemeasuredonlybyaskingresearchparticipantstoprovidethem.Observationsaretypicallypreferredwhenconstructscanbeassesseddirectly.Thesamequestionnairecanbeusedforself-reportsorbyexternalobserversiftheinformationsoughtisthesame.

QuestionnaireTypeInterviewsVersusWrittenQuestionnairesInterviewselicitinformationverballyQuestionnaireselicitinformationinwrittenform.Advantages?Disadvantages?Questionnaire ConstructionQuestionnaireCharacteristicsWhetheradministeredinwrittenformorthroughinterviews,havetwoessentialcharacteristics.Theyhaveitemsdesignedtoelicitinformationofresearchinterest.Theyhaveaprotocolforrecordingresponses.ContentDomainObtainadditionalinformation,suchaspersonaldescriptivecharacteristicsTemptingtoadditemsthatarenotcentraltotheresearchinvestigation–resistit.Attendtodevelopingasetofitemsthatfocusdirectlyandunequivocallyonyourresearchtopic.ItemsItemwordingandthearrangementofitemsaffecttheresponsesobtained.ItemWordingKeeptherespondentinmind.Makeitsimple.Bespecific.Behonest.WordstoAvoidinQuestionnairesAbsolutesAndYouAdjectivestodescribequantityRefertoResearchhighlight4.1,p.44ItemsItemSequenceItishelpfultostartaquestionnairewithitemsthatparticipantsfindinterestingandthatareeasytocomplete.Askfordemographicinformationlast.ScalingOpen-endedresponseformatQuestionnairescalingthathasparticipantsrespondintheirownwords.Closed-endedresponseformatQuestionnairescalinginwhichtheresearcherprovidesparticipantswithfixedresponsecategories.ScalingQuestionnaire ResponseStylesSelf-ReportsTwotendenciesthatinfluenceself-reportresponses:SocialdesirabilityThetendencytopresentoneselfinapubliclyfavorablelight.Responseacquiescence/yea-sayingAtendencytoagreewithastatementregardlessofitscontent.社會期許SocialDesirability名詞解釋:「社會期許」是指在評量個人的性格或態度行為歷程之中，個體常有「假裝完美」(fakegood)的動機，因而常會作假，而傾向於選答能令人產生良好印象的內容，使之符合社會所接納或期許的心態，並不是個體本身真實的內在想法或性格態度。像這種在作答過程中，個人有意製造他人對其產生良好印象，卻非依照本身實際的想法或作法答題的反應心向，即稱之為「社會期許」。為了防止受測者欺騙或作假的反應，人格測驗中常編寫一些相當不確定或中性的題目編入試題中，以誘導受測者產生社會期許心態高低分數，例如「我有時會心情不好」或「我曾說過別人的閒話」等，如果作答結果社會期許分數過高，表示受測者在問卷中過度掩飾自己的真實想法或感受，該人格測驗的結果不盡可靠，而必須重作或作其他類型的人格測驗。ObservationsLeniencyerrorAtendencytosystematicallyprovideamorefavorableresponsethaniswarranted.SeverityerrorAtendencytosystematicallyprovidelessfavorableresponsesthanwarranted,islessfrequent.CentraltendencyerrorPresentwhenanobserverclustersresponsesinthemiddleofascalewhenmorevariableresponsesshouldberecorded.HaloerrorPresentwhenanobserverevaluatesanobjectinanundifferentiatedmanner.PilotTestingTwotypesofpilottestsaredesirable.Onetypeasksindividuals,preferablylikethosewhowillcompletethefinalquestionnaire,toprovidetheirinterpretationandunderstandingofeachitem.Asecondtypeofpilottestismorelikearegularresearchstudy;alargenumberofrespondentsaredesirable.TermstoknowQuestionnairesSelf-reportquestionnairesInterviewsSecondarydataOpen-endedresponseformatClosed-endedresponseformatSocialdesirabilityResponseacquiescenceYea-sayingLeniencyerrorSeverityerrorCentraltendencyerrorHaloerrorForcedchoicescalesMBMZ01ResearchMethodologyChapter5ResearchDesignFoundationsResearchDesignResearchersusetwosourcestohelpdrawcausalinferencesfromrelationshipsobservedamongvariables.Theydrawonconceptualmodelsformulatedtoexplainrelationshipsincausalterms.Theyuseresearchdesignstoassistincausalunderstanding.CausalChallengesInternalCausalCriteriaInternalvalidityispresentwhenvariationinanIVisresponsibleforvariationinaDV.InternalcausalcriteriaIndependentanddependentvariablesaremeaningfullyrelated.Variationintheindependentvariableiscontemporaneouswith,orprecedes,variationinthedependentvariable.Thereisareasonablecausalexplanationfortheobservedrelationshipandarenoplausiblealternativeexplanationsforit.CausalDirection(Simultaneity-Causationisreciprocal)Specification:

UncontrolledVariablesandtheDangerofBiasOthervariablesthatalsoinfluenceincome,suchasyearsofworkexperienceandtypeofoccupation.(Nuisancevariable)NuisancevariableAvariableinthecausalmodelthatisnotcontrolledinaresearchstudy.BiasWhenthecausalrelationshipbetweenanIVandDVisunder-oroverstated.OftenanuncontrolledvariableiscausallyrelatedtotheDVandisrelatedtotheIV,causallyorotherwise.Example,Aresearcherbelievesconsumersatisfactiondependsoncomputerspeed.Greaterspeedisexpectedtoleadtohighersatisfaction.Theresearcherdoesnotaccountforcomputermemoryalsoinfluencessatisfaction.Thelargerthememory,thegreaterthesatisfaction.Computerspeedandmemoryarepositivelyrelated.BiasMemorySatisfactionSpeed+++BiasedRelationMemorySatisfactionSpeed++SpuriousRelationSpuriousRelationshipsOccurswhenannuisancevariableaccountsforalltheobservedrelationshipbetweenadependentandindependentvariable(s).

Anobservedrelationshipbetweenanindependentandadependentvariablebutnocausalrelationship.Examples(fromwikipedia)Anexampleofaspuriousrelationshipcanbeilluminatedbyexaminingacity'sicecreamsales.Thesesalesarehighestwhentherateofdrowningsincityswimmingpoolsishighest.Toallegethaticecreamsalescausedrowning,orvice-versa,wouldbetoimplyaspuriousrelationshipbetweenthetwo.Inreality,aheatwavemayhavecausedboth.Theheatwaveisanexampleofahiddenorunseenvariable,alsoknownasaconfoundingvariable.AnotherpopularexampleisaseriesofDutchstatisticsshowingapositivecorrelationbetweenthenumberofstorksnestinginaseriesofspringsandthenumberofhumanbabiesbornatthattime.Ofcoursetherewasnocausalconnection;theywerecorrelatedwitheachotheronlybecausetheywerecorrelatedwiththeweatherninemonthsbeforetheobservations.HoweverHöferetal.(2004)showedthecorrelationtobestrongerthanjustweathervariationsashecouldshowinpostreunificationGermanythat,whilethenumberofclinicaldeliverieswasnotlinkedwiththeriseinstorkpopulation,outofhospitaldeliveriescorrelatedwiththestorkpopulation.Wikipedia(Chinese)虛假關係:指在兩個沒有因果關係的事件，可能基於其他未見的交絡因素，或潛在變數，顯示出統計學上的相關。

例一統計研究發現，冰淇淋銷量最高的時