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1. Finishing up the bicycles and commute times and SIDS ...frederic/13/F16/day10.pdf1. Finishing up...

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Stat 13, Intro. to Statistical Methods for the Life and Health Sciences. 1. Finishing up the bicycles and commute times and SIDS and Back to Sleep examples. 2. Comparing 2 means, breastfeeding and intelligence example. 3. Paired data and studying with music example. 4. Simulation approach with paired data and baseball example. Read ch7. NO LECTURE THU NOV 3! Review for the midterm will be in class Nov 1. Recall there is also no lecture or office hour Tue Nov 8. Bring a PENCIL and CALCULATOR and any books or notes you want to the midterm and final. HW3 is due Tue Nov 1. 4.CE.10, 5.3.28, 6.1.17, and 6.3.14. In 5.3.28d, use the theory-based formula. You do not need to use an applet. The midterm will be on ch1-7. http://www.stat.ucla.edu/~frederic/13/F16 . 1
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Page 1: 1. Finishing up the bicycles and commute times and SIDS ...frederic/13/F16/day10.pdf1. Finishing up the bicycles and commute times and SIDS and Back to Sleep examples. 2. Comparing

Stat 13, Intro. to Statistical Methods for the Life and Health Sciences.

1.FinishingupthebicyclesandcommutetimesandSIDSandBacktoSleepexamples.2.Comparing2means,breastfeedingandintelligenceexample.3.Paireddataandstudyingwithmusicexample.4.Simulationapproachwithpaireddataandbaseballexample.Readch7.

NOLECTURETHUNOV3!ReviewforthemidtermwillbeinclassNov1.RecallthereisalsonolectureorofficehourTueNov8.BringaPENCILandCALCULATORandanybooksornotesyouwanttothemidtermandfinal.HW3isdueTueNov1.4.CE.10,5.3.28,6.1.17,and6.3.14.In5.3.28d,usethetheory-basedformula.Youdonotneedtouseanapplet.Themidtermwillbeonch1-7.http://www.stat.ucla.edu/~frederic/13/F16.

1

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BicyclingtoWork• WecannotgeneralizebeyondGrovesandhistwobikes.

• Alimitationisthatthisstudyisnotdouble-blind• Theresearcherandthesubject(whichhappenedtobethesamepersonhere)werenotblindtowhichtreatmentwasbeingused.

• Dr.Grovesknewwhichbikehewasriding,andthismighthaveaffectedhisstateofmindorhischoiceswhileriding.How?

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• SIDS.Davies(1985)foundthatinHongKong,wherethecustomwasforchildrentosleepontheirbacks,theratesofSIDSwereverylow.

• 1992:BacktoSleepbeganintheUnitedStates.

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BreastfeedingandIntelligenceExample6.3

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BreastfeedingandIntelligence

• A1999studyin Pediatricsexaminedifchildrenwhowerebreastfedduringinfancydifferedfrombottle-fed.

• 323childrenrecruitedatbirthin1980-81fromfourWesternMichiganhospitals.

• Researchersdeemedtheparticipantsrepresentativeofthecommunityinsocialclass,maternaleducation,age,maritalstatus,andsexofinfant.

• Childrenwerefollowed-upatage4andassessedusingtheGeneral CognitiveIndex(GCI)• Ameasureofthechild’sintellectualfunctioning

• Researcherssurveyedparentsandrecordedifthechildhadbeenbreastfedduringinfancy.

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BreastfeedingandIntelligence

• Explanatoryandresponsevariables.• Explanatoryvariable:Whetherthebabywasbreastfed.(Categorical)

• Responsevariable: Baby’sGCIatage4.(Quantitative)

• Isthisanexperimentoranobservationalstudy?• Cancause-and-effectconclusionsbedrawninthisstudy?

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BreastfeedingandIntelligence

• Nullhypothesis: ThereisnorelationshipbetweenbreastfeedingduringinfancyandGCIatage4.

• Alternativehypothesis: ThereisarelationshipbetweenbreastfeedingduringinfancyandGCIatage4.

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BreastfeedingandIntelligence

• µbreastfed =AverageGCIatage4forbreastfedchildren• µnot =AverageGCIatage4forchildrennotbreastfed

• H0: µbreastfed =µnot• Ha: µbreastfed ≠µnot

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BreastfeedingandIntelligenceGroup Samplesize, n Samplemean Sample SDBreastfed 237 105.3 14.5NotBF 85 100.9 14.0

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BreastfeedingandIntelligence

Thedifferenceinmeanswas4.4.• IfbreastfeedingisnotrelatedtoGCIatage4:

• Isitpossible adifferencethislargecouldhappenbychancealone?Yes

• Isitplausible(believable,fairlylikely)adifferencethislargecouldhappenbychancealone?• Wecaninvestigatethiswithsimulations.• Alternatively,wecanusetheory-basedmethods.

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T-statistic• Tousetheory-basedmethodsinthemultiplemeansapplet,thet-statisticisused.

• Itissimplythenumberofstandarddeviationsourstatisticisaboveorbelowthemeanunderthenullhypothesis.

• 𝑡 = #$%$&#$&'()*+,$)-#&.-/1%23-45 = 6̅8(6̅9(:

;89

<8=;9

9

<9

• Here,t= ?:@.B(?::.C

(8E.F9

9GH =� 8E.I9

JF )

= 2.46.

• p-value~1.4or1.5%.[2*(1-pnorm(2.46))],orusept.

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BreastfeedingandIntelligence

Meaningofthep-value:• IfbreastfeedingwerenotrelatedtoGCIatage4,thentheprobabilityofobservingadifferenceof4.4ormoreor-4.4orlessjustbychanceisabout1.4%.

• A95%CIcanalsobeobtainedusingthet-

distribution.TheSEis (?O.@9

PBQ+

� ?O.:9

S@) =1.79.

SothemarginoferrorismultiplierxSE.

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BreastfeedingandIntelligence

• TheSEis (?O.@9

PBQ+

� ?O.:9

S@) =1.79.Themarginof

errorismultiplierxSE.• Themultipliershouldtechnicallybeobtainedusingthetdistribution,butforlargesamplesizesyougetalmostthesamemultiplierwithtandnormal.Use1.96fora95%CItoget4.40+/- 1.96x1.79=4.40+/- 3.51=(0.89,7.91).

• Thebookuses2insteadof1.96,andtheappletuses1.9756fromthet-distribution.Justuse1.96forthisclass.

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BreastfeedingandIntelligence

• Wehavestrongevidenceagainstthenullhypothesisandcanconcludetheassociationbetweenbreastfeedingandintelligence hereisstatisticallysignificant.

• BreastfedbabieshavestatisticallysignificantlyhigheraverageGCIscoresatage4.

• Wecanseethisinboththesmallp-value(0.015)andtheconfidenceintervalthatsaysthemeanGCIforbreastfedbabiesis0.89to7.91pointshigherthanthatfornon-breastfedbabies.

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BreastfeedingandIntelligence

• Towhatlargerpopulation(s)wouldyoubecomfortablegeneralizingtheseresults?• TheparticipantswereallchildrenborninWesternMichigan.

• Thislimitsthepopulationtowhomwecangeneralizetheseresults.

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BreastfeedingandIntelligence

• CanyouconcludethatbreastfeedingimprovesaverageGCIatage4?• No.Thestudywasnotarandomizedexperiment.• Wecannotconcludeacause-and-effectrelationship.

• TheremightbealternativeexplanationsforthesignificantdifferenceinaverageGCIvalues.

• Whatmightsomeconfoundingfactorsbe?

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BreastfeedingandIntelligence

• CanyouconcludethatbreastfeedingimprovesaverageGCIatage4?• No.Thestudywasnotarandomizedexperiment.• Wecannotconcludeacause-and-effectrelationship.

• TheremightbealternativeexplanationsforthesignificantdifferenceinaverageGCIvalues.• Maybebettereducatedmothersaremorelikelytobreastfeedtheirchildren

• Maybemothersthatbreastfeedspendmoretimewiththeirchildrenandinteractwiththemmore.

• Somemotherswhodonotbreastfeedarelesshealthyortheirbabieshaveweakerappetitesandthismightslowdowndevelopmentingeneral.

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BreastfeedingandIntelligence

• Couldyoudesignastudythatallowsdrawingacause-and-effectconclusion?• Wewouldhavetorunanexperimentusingrandomassignmenttodeterminewhichmothersbreastfeedandwhichwouldnot.(Itwouldbeimpossibletodouble-blind.)

• Randomassignmentroughlybalancesoutallothervariables.

• Isitfeasible/ethicaltoconductsuchastudy?

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StrengthofEvidence• Wealreadyknow:

• Assamplesizeincreases,thestrengthofevidenceincreases.

• Justaswithproportions,asthesamplemeansmovefartherapart,thestrengthofevidenceincreases.

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MoreStrengthofEvidence• Ifthemeansarethesamedistanceapart,butthestandarddeviationschange,thenthestrengthofevidencechangestoo.

• Whichgivesstrongerevidenceagainstthenull?

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MoreStrengthofEvidence• Ifthemeansarethesamedistanceapart,butthestandarddeviationschange,thenthestrengthofevidencechangestoo.

• Whichgivesstrongerevidenceagainstthenull?

• Smaller SDs lead to stronger evidence against the null.

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EffectsonWidthofConfidenceIntervals

• Justasbefore:• Assamplesizeincreases,confidenceintervalwidthstendtodecrease.

• Asconfidencelevelincreases,confidenceintervalwidthsincrease.

• Thedifferenceinmeanswillnotaffectthewidth(marginoferror)butwillaffectthecenteroftheCI.

• Aswesawwithasinglemean,astheSDsofthesamplesincrease,thewidthoftheconfidenceintervalwillincrease.

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PairedData.Chapter7

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Introduction• Thepaireddatasetsinthischapterhaveonepairofquantitativeresponsevaluesforeachobs.unit.

• Thisallowsforacomparisonwheretheotherpossibleconfoundersareassimilaraspossiblebetweenthetwogroups.

• Paireddatastudiesremoveindividualvariabilitybylookingatthedifferencescoreforeachsubject.

• Reducingvariabilityindataimprovesinferences:• Narrowerconfidenceintervals.• Smallerp-valueswhenthenullhypothesisisfalse.• Lessinfluencefromconfoundingfactors.

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3.Paireddataandstudyingwithmusicexample.Example7.1

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StudyingwithMusic• Manystudentsstudywhilelisteningtomusic.• Doesithurttheirabilitytofocus?• In“CheckingItOut:Doesmusicinterferewithstudying?”StanfordProfCliffordNass claimsthehumanbrainlistenstosonglyricswiththesamepartthatdoeswordprocessing.

• Instrumentalmusicis,forthemostpart,processedontheothersideofthebrain,andNassclaimsthatlisteningtoinstrumentalmusichasvirtuallynointerferenceonreadingtext.

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StudyingwithMusicConsidertheexperimentaldesigns:ExperimentA — Randomassignmentto2groups• 27studentswererandomlyassignedto1of2groups:

• Onegrouplistenstomusicwithlyrics.• Onegrouplistenstomusicwithoutlyrics.

• Studentsplayamemorizationgamewhilelisteningtotheparticularmusicthattheywereassigned.

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StudyingwithMusicExperimentB— Paireddesignusingrepeatedmeasures• Allstudentsplaythememorizationgametwice:

• Oncewhilelisteningtomusicwithlyrics• Oncewhilelisteningtomusicwithoutlyrics.

ExperimentC— Paireddesignusingmatching• Sometimesrepeatingsomethingisimpossible(liketestingasurgicalprocedure)butwecanstillpair.• Testeachstudentonmemorization.• Matchstudentsupwithsimilarscoresandrandomly:

• Haveoneplaythegamewhilelisteningtomusicwithlyricsandtheotherwhilelisteningtomusicwithoutlyrics.

Page 29: 1. Finishing up the bicycles and commute times and SIDS ...frederic/13/F16/day10.pdf1. Finishing up the bicycles and commute times and SIDS and Back to Sleep examples. 2. Comparing

StudyingwithMusicWewillfocusontherepeatedmeasurestypeofpairing.• Whatifeveryonecouldrememberexactly2morewordswhentheylistenedtoasongwithoutlyrics?

• UsingExperimentA,therecouldbealotofoverlapbetweenthetwosetsofscoresanditwouldbedifficulttodetectadifference,asshownhere.

Without Lyrics

With Lyrics

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StudyingwithMusic• Variabilityinpeople’smemorizationabilitiesmaymakeitdifficulttoseedifferencesbetweenthesongsinExperimentA.

• Thepaireddesignfocusesonthedifference inthenumberofwordsmemorized,insteadofthenumberofwordsmemorized.

• Bylookingatthisdifference,thevariabilityingeneralmemorizationabilityistakenaway.

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StudyingwithMusic• InExperimentB,therewouldbenovariabilityatallinourhypotheticalexample.

• Whilethereissubstantialvariabilityinthenumberofwordsmemorizedbetweenstudents,therewouldbenovariabilityinthedifferenceinthenumberofwordsmemorized.Allvalueswouldbeexactly2.

• Hencewewouldhaveextremelystrongevidenceofadifferenceinabilitytomemorizewordsbetweenthetwotypesofmusic.

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PairingandRandomAssignment

• Pairingoftenincreasespower,andmakesiteasiertodetectstatisticalsignificance.

• Canwemakecause-and-effectconclusionsinpaireddesign?

• Shouldwestillhaverandomassignment?

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PairingandRandomAssignment

Inourmemorizingwithorwithoutlyricsexample:• Ifweseesignificantimprovementinperformance,isitattributabletothetypeofsong?

• Whataboutexperience?Couldthathavemadethedifference?

• Whatisabetterdesign?• Randomlyassigneachpersontowhichsongtheyhearfirst:withlyricsfirst,orwithout.

• Thiscancelsoutan“experience”effect

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ParingandObservationalStudies

Youcanoftendomatchedpairsinobservationalstudies,whenyouknowthepotentialconfounderaheadoftime.Ifyouarestudyingwhethertheportacaval shuntdecreasestheriskofheartattack,youcouldmatcheachpatientgettingtheshuntwithapatientofsimilarhealthnotgettingtheshunt.Ifyouarestudyingwhetherlefthandedness causesdeath,andyouwanttoaccountforageinthepopulation,youcouldmatcheachleftiewitharightie ofthesameage,andcomparetheiragesatdeath.

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4.Simulation-BasedApproachforAnalyzingPairedData,androundingfirstbaseexample.Section7.2

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RoundingFirstBaseExample7.2

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RoundingFirstBase• Imagineyou’vehitalinedriveandaretryingtoreachsecondbase.

• Doesthepaththatyoutaketoroundfirstbasemakemuchofadifference?• Narrowangle• Wideangle

Narrow

Wide

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RoundingFirstBase

• Woodward(1970)investigatedthesebaserunningstrategies.

• Hetimed22differentrunnersfromaspot35feetpasthometoaspot15feetbeforesecond.

• Eachrunnerusedeachstrategy(paireddesign),witharestinbetween.

• Heusedrandomassignmenttodecidewhichpatheachrunnershoulddofirst.

• Thispaireddesigncontrolsfortherunner-to-runnervariability.

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FirstBase• Whataretheobservationalunitsinthisstudy?

• Therunners(22total)• Whatvariablesarerecorded?Whataretheirtypesandroles?• Explanatoryvariable:baserunningmethod:wideornarrowangle(categorical)

• Responsevariable:timefromhomeplatetosecondbase(quantitative)

• Isthisanobservationalstudyoranexperiment?• Randomizedexperiment.

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Theresults

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TheStatistics

• Thereisalotofoverlapinthedistributionsandsubstantialvariability.

• Itisdifficulttodetectadifferencebetweenthemethodswhentheseissomuchvariation.

Mean SDNarrow 5.534 0.260Wide 5.459 0.273

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RoundingFirstBase

• However,thesedataareclearlypaired.• Thepairedresponsevariableistimedifferenceinrunningbetweenthetwomethodsandwecanusethisinanalyzingthedata.

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TheDifferencesinTimes

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TheDifferencesinTimes

• Meandifferenceis�̅�d=0.075seconds• StandarddeviationofthedifferencesisSDd =0.0883sec.

• Thisstandarddeviationof0.0883issmallerthantheoriginalstandarddeviationsoftherunningtimes,whichwere0.260and0.273.


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