社会调查与研究方法 - week 13

社会调查与研究方法

SociologicalResearchMethods浙江大学2016年春夏学期任课教师：曹洋Chapter13:QualitativeDataAnalysis（定性资料分析）IntroductionQualitativeanalysis:MethodsforexaminingsocialresearchdatawithoutconvertingthemtoanumericalformatFocusofthischapter:DevelopingexplanationsThisrequiresthediscoveryofpatternsNote:sometimesqualitativeresearchisundertakenfordescriptivepurposes,e.g.,ethnography.Contrastwithquantitativeanalysis:Quantitativeanalysis:Theory–hypothesis–datacollection–empiricaltestQualitativeanalysis:Theory–analysis–theory–analysis……LinkingTheoryandAnalysis:

DiscoveringPatterns–1Sixwaysoflookingforpatterns(Loflandetal.2006):FrequencyMagnitudeStructuresProcessesCausesConsequencesExamples:ChildabuseCorporatedownsizingLinkingTheoryandAnalysis:

DiscoveringPatterns–2Cross-caseanalysis:Variable-orientedanalysis:Beginwithbasic/importantcharacteristics&seeiftheyarerelatedtotheoutcomeofinterestMorerelatedtonomotheticexplanationsCase-orientedanalysis:Examineeachcaseindepth&seeifitpointstomoregeneralsociologicalconceptsorvariablesMorerelatedtoidiographicexplanationsBothmethodsareinductiveinnatureLinkingTheoryandAnalysis:

GroundedTheoryMethod(GTM)Groundedtheorymethod:Theoriesaregeneratedsolelyfromanexaminationofdata,ratherthanbeingdeducedfromassumptionsorpriorconclusionsInductiveapproachatitsextremeLinkingTheoryandAnalysis:

ConstantComparativeMethodComparingincidentsapplicabletoeachcategoryEssentiallyaboutidentifyingimportantconceptsIntegratingcategoriesandtheirpropertiesExpandfromconceptstopossiblecausesandconsequencesDelimitingthetheorySolidifyandextendtheoryWritingtheoryForpresentation,andalsoanotherstepofrefinementLinkingTheoryandAnalysis:

SemioticsSemiotics:thescienceofsignsHastodowithsymbolsandmeaningSymbolsincludelanguages,etiquette,emoticons,mascots,etc.OftenassociatedwithcontentanalysisSymbolshavenoinherentmeanings;theirmeaningsaresociallyconstructedExample:colorschemesforwedding,stockquotes,etc.SemioticanalysisisthesearchformeaningseitherintentionallyorunintentionallyattachedtosignsExample:GenderAdvertisements,byErvingGoffmanGenderdifferencesinsizeandplacementAllreflectspower,status,andsocialworthLinkingTheoryandAnalysis:

ConversationAnalysisConversationanalysis:Ameticulousanalysisofthedetailsofconversation,basedonacompletetranscriptthatincludespauses,hems,haws,etc.OftenassociatedwithethnomethodologySomebasics(Solverman1993):ConversationissociallystructuredConversationmustbeunderstoodcontextuallyCAisbasedonexcruciatinglydetailedandaccuratetranscriptsExample:communicationofsafesexinformationatanHIVtestingclinic(Kinnell&Maynard1996)QualitativeDataProcessingCoding:classifyingorcategorizingindividualpiecesofdataCenteredaroundconceptsMustbecoupledwithanidentificationandretrievalsystemCodinginstages:Opencoding:initialidentificationofconceptsthatappearinthedataAxialcoding:toidentifysomegeneral,importantconceptsSelectivecoding:identificationofcentralconceptsEachunitcanhavemorethanonecodeandsometimeshierarchicalcodingisappropriateSkim:memoing,conceptmapping,andcomputersoftware(skim)Chapter14:QuantitativeDataAnalysis(定量资料分析)OverviewPurposeofquantitativedataanalysis:description&explanationQuantificationofdata:preparationstepUnivariateanalysis:examinesasinglevariableUsuallyfordescriptivepurposesBivariateanalysis:examinestherelationshipbetweentwovariablesTosetuparesearchquestion;orToprovidesomepreliminaryexplanationMultivariateanalysis:examinesmorethantwovariablessimultaneouslySomeexamplesDataQuantificationPreparingthedata:Convert“rawdata”intonumericalformCreatemachine-readabledatafile(dataentry,opticalscan,etc.)RecodevariableswithappropriatecategoriesDocumentationQuantificationofdata:Intervalandratiovariables:recordthenumericalvaluesNominalandordinalvariables:assignnumberstocategoriesNeedtokeeparecordofwhichnumberrepresentswhatExample:gender1-male2-femaleMaintaindetailedcategoriesatthebeginningDetailedcategoriescanalwaysbecombinedintobroaderones,notviceversaExample:seeoccupationalcategoriesat/soc/soc_majo.htm

TwoApproachesinCodingVariablesApproach1:usepredeterminedcodingschemesCodingbasedontheoreticalconsiderationsEx:white-collarvs.bluecollar;self-employmentvs.other;etc.FollowingestablishedcodingschemeThisallowsforbettercommunicationandeasycomparisonApproach2:generatecategoriesfromthedataThisapproachisespeciallyappropriatewhendatacomefromopen-endedquestionsTheoreticalconceptsandthepurposeofthestudybecomeevenmoreimportantCodebookConstructionElectronicdatafilesandstatisticalprogramsidentifyvariablesusingabbreviatednamesAcodebookcontainsalistofvariablesandprovidesallessentialinformationabouthoweachvariableiscoded.VariablenameWhataretheresponsecategoriesWhatarethenumericallabelsCodeformissingdataEtc.APartialCodebookGENDER:whatisyourgender?1.male2.femaleEDUC:howmanyyearsofeducationdoyouhave?0through25-99.don’tknow/noanswerDEGREE:whatisyourhighestdegree?1.lessthanhighschool2.highschool3.associatedegree4.bachelor’sdegree5.post-graduate9.don’tknow/noanswerAGE:howoldareyou?0through120-99.don’tknow/noanswerATTEND:howoftendoyouattendreligiousservices?0.never1.lessthanonceayear2.aboutonceortwiceayear3.severaltimesayear4.aboutonceamonth5.2-3timesamonth6.nearlyeveryweek7.everyweek8.severaltimesaweek9.don’tknow/noanswerWhatDataLookLikeIDGENDEREDUCDEGREEAGEATTEND121223372117425031916264216479152195406621222937112219581143241...UnivariateAnalysisDescribethedistributionofasinglevariable:Distribution:howthecasesinthedataaredistributedacrossdifferentvaluesorcategoriesExample:givenarandomsampleof200workers,wecanexaminethefollowing:Gender:howmanymalesandhowmanyfemalesAge:howmanyintheir20s,30s,40s,50s,&60sRace:howmanyarewhite,black,Hispanic,Asian,etc.Occupation:howmanyblue-collar,white-collar,etc.Industry:howmanyintobacco,banking,airlines,etc.TechniquesforUnivariateAnalysisFrequencydistributionChartsandgraphsStatisticalmeasuresFrequencydistribution:attendLabelValueFrequencyPercentValidpercentCumpercentNever047116.716.816.8<onceayear11987.07.123.9Onceayear239614.114.138.0Severaltimesayear337113.213.251.3Onceamonth41916.86.858.12-3timesamonth52559.19.167.2Nearlyonceawk61696.06.073.2Everyweek750818.118.191.4>Onceaweek82428.68.6100.0DK,NA9110.4--TotalValidcases2,812missing:11BarChart:HowoftenpeopleattendreligiousservicesUnivariateStatisticsMeasuresofcentraltendency:MeanModeMedianPercentiles/quartilesMeasuresofdispersion:IndexofqualitativevariationStandarddeviationContinuousvs.DiscreteVariablesAcontinuousvariablecanincreaseordecreasecontinuouslybyanyfractionAndfractionsarealwaysmeaningfulAdiscretevariablehavediscretevaluesorcategoriesContinuous-discretevs.levelofmeasurement:NominalOrdinalIntervalRatioContinuousNANAtemperatureIncomeDiscretegenderdegree???#ofchildrenAdditionalIssuesDetailvs.manageabilityinpresentingyourdata:PresentingtoolittleinformationgoesagainstthepurposeofdescriptionPresentingtoomuchinformationmayoverwhelmthereaderanddistractattentionfromthemostimportantaspectsHandling“don’tknows”Sometimes“don’tknow”isanimportantcategoryExample:publicopinionresearchisofteninterestedinhowinformedpeopleareofacertainissueSometimes“don’tknow”indicatesuncooperativerespondentOthertimes“don’tknow”maybeclosetomeaninglessDecisionneedstobemadeonacase-by-casebasisBivariateAnalysisExaminestherelationshipbetweentwovariablesAimedatdiscoveringpatternsCanbeusedfortheorytestingorforinductivetheoryconstructionContingencytables:Across-tabulationofcaseswithtwovariablesNorm:IVcategoriesincolumns,DVcategoriesinrowsPresentbothfrequenciesandcolumnpercentagesMostappropriatewhentheIVandDVaremeasuredatthenominalorordinallevelSubgroupcomparisonSubgroupComparisonsAtypeofbivariateanalysisTheentiresampleisdividedintosubgroupsbasedontheindependentvariableComparisonsarema