Chapter 24 - Logistic regression

Chapter 24 - Logistic regression

ID:40600119

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时间:2019-08-04

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1、Chapter24LogisticRegressionContentlistPurposeoflogisticregression568Assumptionsoflogisticregression569Thelogisticregressionequation570Interpretinglogoddsandoddsratio573ModelÞtandlikelihoodfunction574SPSSactivityÐalogisticregressionanalysis575Bytheendofthischapteryo

2、uwillunderstand:1Thepurposesoflogisticregression.2HowtouseSPSStoperformlogisticregression.3HowtointerprettheSPSSprintoutoflogisticregression.IntroductionThischapterextendsourabilitytoconductregression,inthiscasewheretheDVisanominalvariable.Ourpreviousstudiesonregre

3、ssionhavebeenlimitedtoscaledataDVs.ThepurposeoflogisticregressionThecruciallimitationoflinearregressionisthatitcannotdealwithDV’sthataredichoto-mousandcategorical.Manyinterestingvariablesinthebusinessworldaredichotomous:forexample,consumersmakeadecisiontobuyornotbu

4、y,aproductmaypassorfailqualitycontrol,therearegoodorpoorcreditrisks,anemployeemaybepromotedornot.Arangeofregressiontechniqueshavebeendevelopedforanalysingdatawithcategoricaldependentvariables,includinglogisticregressionanddiscriminantanalysis(DA)(Chapter25).Logisti

5、calregressionisregularlyusedratherthanDAwhenthereareonlytwocategoriesofthedependentvariable.LogisticregressionisalsoeasiertousewithSPSSthanDAwhenthereisamixtureofnumericalandcategoricalIV’s,becauseitincludesproceduresforgeneratingthenecessarydummyvariablesautomatic

6、ally,requiresfewerassumptions,andismorestatisticallyrobust.DAstrictlyrequiresthecontinuousindependentvariablesLOGISTICREGRESSION569(thoughdummyvariablescanbeusedasinmultipleregression).Thus,ininstanceswheretheindependentvariablesarecategorical,oramixofcontinuousand

7、categorical,andtheDViscategorical,logisticregressionisnecessary.Logisticregression.Determinestheimpactofmultipleindependentvariablespresentedsimultaneouslytopredictmembershipofoneorotherofthetwodependentvariablecategories.Sincethedependentvariableisdichotomouswecan

8、notpredictanumericalvalueforitusinglogisticregression,sotheusualregressionleastsquaresdeviationscriteriaforbestfitapproachofminimizingerroraroundt

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