多個(gè)樣本率的卡方檢驗(yàn)與兩兩比較之spss超簡(jiǎn)單

1、SPSS :多個(gè)樣本率的卡方檢驗(yàn)及兩兩比擬來(lái)自：醫(yī)咖會(huì)醫(yī)咖會(huì)之前推送過(guò)“兩個(gè)率的比擬 (卡方中金驗(yàn))及Fisher精確檢驗(yàn)的SPSS教程,小 伙伴們都掌握了嗎？如果不止兩個(gè)分組,又該如何進(jìn)行卡方檢驗(yàn)以及之后的兩兩比擬呢？來(lái)看詳細(xì)教程吧！1、問(wèn)題與數(shù)據(jù)某醫(yī)生擬探討藥物以外的其他方法是否可降低患者的膽固醇濃度,如增強(qiáng)體育鍛煉、減少體重及改善飲食習(xí)慣等.該醫(yī)生才H募了 150位高膽固醇、生活習(xí)慣差的受試者,并將其隨機(jī)分成3組.其中一組給予降膽固醇藥物,一組給予飲食干預(yù),另一組給予運(yùn)動(dòng)干預(yù).經(jīng)過(guò)6個(gè)月的試驗(yàn)后,該醫(yī)生重新測(cè)量受試者的膽固醇濃度,分為高和正常兩類(lèi).該醫(yī)生收集了受試者接受的干預(yù)方法(int

2、ervention )和試驗(yàn)結(jié)束時(shí)膽固醇的風(fēng)險(xiǎn)程度(risk_level )等變量信息,并根據(jù)分類(lèi)匯總整理,局部數(shù)據(jù)如下：lridividuai scores for eoch participantTotot coum data (frequenciesch.-frqi-srs-tesA-cf-hzmisgmity-iiXFual-kF域 cht-iqL j： &-lat-cf-hem09e eity-2il.s.Jb1 Cdt£Setl - IBM SPSS itaListiiFjieRaia r-jn;fomi 苫"飛Fi ft Edit Jeta匚對(duì)向Tr.

3、=msfrirri 研瑞門(mén)？ GrfiDli5 Uhl空的阻|l54' risijeuei1(iItiv- tijirickjfff*intQntiDn能也1的| frsqTDrvffHigh1Dh)aHigfiIE2 IDrtgHigh2DrugNormal343口 rtgHigh3DietHyi2fi4口3 qUgh4DietNomai225口 n.gFhgb5Hi 53C&DFLftHigh6EfflfdaeNomsi207_DmgHigh_lB口 rugHigh' "1&CMhighWOfljH 附1TDflqHigh12DrgHighJ3Dr

4、ugHighliD&gHigh15OrLffFhgh_16DrugUgh17|口也 gNarmM18DregNnrnal19口 rugN(xnn 最2QDrug注釋?zhuān)罕狙芯繉⒛懝檀紳舛确譃椤案吆汀罢深?lèi),只是為了分析的方便, 并不代表臨床診斷結(jié)果.2、對(duì)問(wèn)題的分析研究者想判斷干預(yù)后多個(gè)分組情況的不同.如本研究中經(jīng)過(guò)降膽固醇藥物、飲食和運(yùn)動(dòng)干預(yù)后,比擬各組膽固醇濃度的變化情況.針對(duì)這種情況,我們建議使用卡方檢驗(yàn)2X0,但需要先滿足5項(xiàng)假設(shè)：假設(shè)1 :觀測(cè)變量是二分類(lèi)變量,如本研究中試驗(yàn)結(jié)束時(shí)膽固醇的風(fēng)險(xiǎn)程度變量是二分 類(lèi)變量.假設(shè)2:存在多個(gè)分組 2個(gè),如本研究有 3個(gè)不同的干預(yù)組.假

5、設(shè)3:具有相互獨(dú)立的觀測(cè)值,如本研究中各位受試者的信息都是獨(dú)立的,不會(huì)相互 干擾.假設(shè)4:研究設(shè)計(jì)必須滿足：a樣本具有代表性,如本研究在高膽固醇、生活習(xí)慣差 的人群中隨機(jī)抽取150位受試者；b目的分組,可以是前瞻性的,也可以是回憶性的, 如本研究中將受試者隨機(jī)分成 3組,分別給予降膽固醇藥物、飲食和運(yùn)動(dòng)干預(yù).假設(shè)5:樣本量足夠大,最小的樣本量要求為分析中的任一預(yù)測(cè)頻數(shù)大于5.經(jīng)分析,本研究數(shù)據(jù)符合假設(shè)1-4 ,那么應(yīng)該如何檢驗(yàn)假設(shè) 5,并進(jìn)行卡方檢驗(yàn)2 X 0呢？3、思維導(dǎo)圖4、SPSS操作4.1 數(shù)據(jù)加權(quán)在進(jìn)行正式操作之前,我們需要先對(duì)數(shù)據(jù)加權(quán),如下:(1)在主頁(yè)面點(diǎn)擊 Data 一 Wei

6、ght Cases(2)點(diǎn)擊 Weight cases by ,激活 Frequency Variable 窗口(3)將 freq 變量放入 Frequency Variable 欄(4)點(diǎn)擊OK4.2 檢驗(yàn)假設(shè)5數(shù)據(jù)加權(quán)之后,我們要判斷研究數(shù)據(jù)是否滿足樣本量要求,如下:fCrosstabs在主頁(yè)面點(diǎn)擊 Analyze Descriptive StatisticsS of- proportionsin-sp»-lndiv1dudl-scoreu« DauSttlj IBM SPSS 5tadstki Data EdtorFie Edit r/iew口 ataTransfom

7、 Analyze Graphs Unities Add-on 5 Window HepRe£ort3卜麗案EfflkLr？i ',tH3Descrtotrve Statists匚 Frequencies3 y鬻：in闌venhon1rionpare Means卜inter«niionrisk, levelGeneral Linear Model4 Eipiore.1DrugHi中卜Generalized Linear ModelsQ C'osstabs.2DwgHiyiMixed Models3DiugHignCorrelate卜TURF Analysis4

8、DmgHi串RegressionLo clin ear國(guó) Ratio.5D(ugHifi卜Plots.GrugHiiClassyF國(guó) Q Q Plots .1tigHignDimensiofi R&dLdicnScsleUonp aram etric T sstsForecaspngaDrugHi第gDrugH卬10口 mgHiTiiDrugHi*iF12DrugHignSur/ivd13DnjgUuNipie Respon&e樣 Simulazion.14DgHi甲15DiuqHighQuall Control1fiDrjqHifPS ROC Curve17 i1Drug川于

9、彈出下列圖:(2)將變量 intervention 和 risk_level 分別放入 Row(s)欄和 Column(s)欄(3)點(diǎn)擊Statistics ,彈出下列圖:望 Crosstabs: Statistics0 iChi*squarei 口 Correlatiions-NominalContingency coelficientPhi anti Cramer's V二 LambdaUncertain coefficient-OrdinalEl GarnrnaSomers' d匚 KendalPs tau-b Kendall's taucNominal by I

10、ntervalEfeKappa RiskTylcNemarCochran and Mantel-HaenszEl statisticsTest SQinmcn odds ratio &ciiials: iContinue Cancel Help _ 、(4)點(diǎn)擊 Chi-square Crosstabs: StatisticsXiSiChi-square| 口 CorrelationsIisthiaiiim j-,urrmi mn inw -snrt4!-Nominali Contingency coefficient1 J Phi and Cramers V,L_ LambdaUnc

11、ertainty coefTicientNominal by Interval Eta-Ordinal-GarnrnaSomers' d Kendalls lau-b.KendalFs tau-c.Kappa RiskMcNerriarCochran's and Mantel-Haenszel statisticsTest cofTifnori cdds ratio &ousls: iCcntinueJ Cancel H&lp(5)點(diǎn)擊 Continue Cells(6)點(diǎn)擊Counts欄中的Expected 選項(xiàng)(7)點(diǎn)擊 Continue 一 OK經(jīng)上述操作

12、,SPSS輸出預(yù)期頻數(shù)結(jié)果如下:Level of cholesterol risk: "High" & "Normal"" Type of intervention: "Drug*',MDiet*1 & "Exercise11 CrosstabulationExpected CouniType of intervention: "Drug", ''Diet' & "Exercise"DrugDietExerciseTotalL&a

13、mp;vel af cholesterol risk:Higti" t' Nornnal"High24.724.724.7740Ncrmal25.325.325；7S.0Total50.050.050 0150.0該表顯示,本研究最小的預(yù)測(cè)頻數(shù)是24.7,大于5,滿足假設(shè)5,具有足夠的樣本量.Chi-Square Tests表格也對(duì)該結(jié)果做出提示,如下標(biāo)注局部：Chi-Square TestsValuedfAsymptotic Significance (2-sided)Pearson Chi-Square9 175d2.010Likelihood Ratio9.3

14、362(JOSLinear-by-LinearAssociation7 7691.00511 ofValid Cases150I a. 0 cells (0 0%) have expected count less than 5.| minim urn expected uoLnlir 24 mThe即在本研究中,沒(méi)有小于 5的預(yù)測(cè)頻數(shù),可以直接進(jìn)行卡方檢驗(yàn)(2 X C).那么,如果存在預(yù)測(cè)頻數(shù)小于 5的情況,我們應(yīng)該怎么辦呢？ 一般來(lái)說(shuō),如果預(yù)測(cè)頻數(shù)小于 5,就需要進(jìn)彳t Fisher精確本金驗(yàn)(2 x C),我們將在后面推送的內(nèi)容中向大家詳細(xì)介紹.4.3 卡方檢驗(yàn) (2 X C)SPSS操

15、作1 l葉-i f-p i： ii l ；n ir'i ：i .1 !-i -I -".1 - "F- '"P 丁 -l r1- t i F |i- irE的巨山1£人W DaCJTrdiiirm蟲(chóng)mb四&批i.ULIi'Ul. /中劃二WkldowHQla匚圜,TrL4減些art?k,.片g a j1HD Q£ CnDllW：匕u cs幟比 Dt£i2TjpLeS.% E.Ch：roflCrocgtabj. qCoripMsi豈 Mean&LnearrAcdeJ3口54m附口.悟)35 就 W

16、gfllleTiiKgf>en:on3 *_匚GeierslG9B 例I1OnjgHighWDm3HighMdiuod«is| 3DinuHigh殳加閘小Lggfiiw和*D im sn <i tWL Q* rturt on,TuAF Analysis 二皮1mH P-P Ptote.力an p Qts1_4口 rugHighGO*ugHigh6CaigiHigh7Dnj0high匚6口 njgHigh3留白h1of=pal3卜9Mi 口HighmeircTesisin 3笛DwgHigh11DwgHigh12DwgHigh亙U!譚N還13Um 口High)nu.ionl

17、rol?且U口 njgHighgimjlat:15Dm&High包的c16CnjgHighROC Cur17bugHigh彈出下列圖: Crosstabs: StatisticsXiSiChi-square Correlationsinmi rB-rt! r-s,rrr,m inw -sOrdinal-GarnrnaSomers' dKendalls lau-BH Kendalls tau學(xué)-Nominal-Contingency coefficientPtii and Cramers V匚 LambdaUncert3inh, coefTicientNominal Dy Int

18、ervalKappa EtaE RiskWcNemarCochran's and Mantel-HaenszEl statistics Test cofTunon odds ratio &qusIs: iCcntinu C a n g&I H 對(duì)口 . i .(5)點(diǎn)擊Percentage 欄中的Column 選項(xiàng)CountsjibravBiimni “ram ran 1* rniiiiaHriHiirpbservedExpectedl Hide small countsLess ttiari eI Percentages-I Row,Column| El Total址

19、 Crosstabs Cell Display於test.Compare colJinn proportions Adjust p-values (Banferroni rnethod-ResidualsUnElsndardizedL.j StandsrCized| Adjustedstandardiz&d-Noninte ger WeiQhte® Round cell counts © Round case weightsTruncate c«ll counts Q Truncate case weighlsNo adijuslnnents£o

20、rtinu& Cancel Help4.4組間比擬境 tert - of - pro pc it c n 3- in - sps 5- ndi/idud scores, jibv Detiirtl - IBM SPSS Statistics Dots Edt&rFil ft Edt ' 鳴/DataTransform .Mahrze Graphs Utilities Add-ons Window Hdp* R*ptU+博3 2 j uEE3 A *a口上“二附 31ahstin卜Fl Pr5CEJsrratE.36: ntarv£fit<>n1二吧

21、蜉白Mgan£ n10 0 MpiVF¥,_intsrvfrntisnnek l 中j*IConoral Uim1rMl川Gene lai LadLlnsd Models4 pl ore.1,1口 rugHighEf Crosstsjs .TUR" Anasis23DrugDrugHighmi蕈aK"日im卜Correlate4DrughighRzte&sioli卜H Ratio.5DrugHighLgir)6 2Cl335if?Olrnenskn Redurfn0對(duì)qkN&nparaneTic Taste卜cr之*nJSurvvaJMu

22、ltiple R目部ioti5后導(dǎo)電nuim.QuflliVCcrtiQl卜可 ROC Cufya.1 1 F-H HiOU.6DrugHigh|1Q-Q 弓口始.1OUQUgh JC9DrugDrugHghHghIQrugHigh1112EDrug_g J High13DrugNgh14DrugHigh16IS:DrugDrugHgh卜謝irDrughigh彈出下列圖:(2)點(diǎn)擊Cells ,彈出下列圖:(3) 點(diǎn)擊 z-test 欄中的 Compare column proportions(Bonferroni method) 選項(xiàng)和 Adjust p-values(4)5、結(jié)果解釋5.1

23、 統(tǒng)計(jì)描述在進(jìn)行卡方檢驗(yàn)(2 X C)的結(jié)果分析之前,我們需要先對(duì)研究數(shù)據(jù)有個(gè)根本的了解.SPSS輸出結(jié)果如下：riskjevel * int«rverition CrosstabnlationirtefvenrtioriTotalDrugDietExerciserishlevel HighCount16a28b3 口b74Expected Count24.724724774.0% within intervention32.0%56.0%60.0%49.3%Nornnal Count3褊22tr20b76E印nt我Count25.3P 25325.376.0% within int

24、erventipri阻口氣44.柏4./501漏TotalCount5050SO150 Expected Count50. 050.050.015D.0% within ini4iventionMOP聃100.0%100.0%100.0%Each subscript letter denotes a subset of intervention categories whose column proportions do notdifFer significantly from each other at the .05 level.該表提示,本研究共有 150位受試者,根據(jù)干預(yù)方式均分為3組

25、.在試驗(yàn)結(jié)束時(shí),藥物干預(yù)組的50位受試者中有16位膽固醇濃度高,飲食干預(yù)組的50位受試者中有28位膽 固醇濃度高,而運(yùn)動(dòng)干預(yù)組的50位受試者中有30位膽固醇濃度高,如下標(biāo)注局部：riskjml' inteiwrition Crosstabulavioni interwen tianTotalDrugDietExerciseriskjevel HighCount出28b孫74Expected Count24724724.774.0% with in intervention32.0%56.0%60.C%49.3%Normal Count34a22b20l76Expected Count2

26、5 325325.375.0% wrthin interventionee o%4-4 C%40.0%50,796TotalCount5C50150Exp&cted Count50 050050.0155.0% within intervention100 0%100.0%100.C%100.0%Each subscript letter denotes a subset of int&rventlon categories whcs colurriii proportions do not differ significantly from each other atilie

27、 05 lev&l.由此可見(jiàn),藥物干預(yù)比飲食或運(yùn)動(dòng)干預(yù)的療效更好.同時(shí),該表也提示, 藥物干預(yù)組的50位受試者中有34位膽固醇濃度下降, 飲食干預(yù)組的50位受試者中有22位膽固醇濃度 下降,而運(yùn)動(dòng)干預(yù)組的 50位受試者中只有20位膽固醇濃度下降,如下標(biāo)注局部：risk leviel H iirtervention CrosstabulntioninterventionTotalDugDietExerciseriskjevel HighCourrt15a2Sb3Db74Expected Count24.724.724774 0% within int&rvention32.0%5

28、6.0%60.0%49.3%Normal Count34a22b2Db76Expected Count25.325.32537«,Q% within InterverWon阻口現(xiàn)4409t40.0%507%TotalCtjunrt5C5050150Expected Count50.050.0500150.0%witliin intenention100 0%100036100.0%100.0%Each subscript letter denctes a subset of Intersantion categories whose column proportions do not

29、 differ significantly from each othrat th& .05 level.但是,當(dāng)各組樣本量不同時(shí),頻數(shù)會(huì)誤導(dǎo)人們對(duì)數(shù)據(jù)的理解.因此,我們推薦使用頻率來(lái)分析結(jié)果,如下標(biāo)注局部：risklevel 1 iriteivention CrosstabulationintarventionDrug口伯tExerciseTotalriskjevelHighCount16a28b30b74EKpeeted Count24.724 74.774.0% within Intervention32.0%56.0%60 0%49 3%NormalCount34,及b20b7

30、6Expected Count25.325.325376.0% within inteiveniion69.0%44.0%P 40.0%507%TotalCount505 口50150Bep“怡W Count50.050.0500150.0% wittiin interveniion10D0%100.0%1Q0 口陽(yáng)100.0%Eich subscriptlelterdenotes a subset ofintervention categories whose column proportions do not differ signlficanuyfroni 03ch oiher at t

31、he .05 loel.該表提示,藥物干預(yù)組的50位受試者中68%膽固醇濃度下降,飲食干預(yù)組的50位受試者中44%膽固醇濃度下降,而運(yùn)動(dòng)干預(yù)組的50位受試者中只有 40%膽固醇濃度下降,提示藥物干預(yù)比飲食和運(yùn)動(dòng)干預(yù)更有效.但是這種直接的數(shù)據(jù)比擬可能受到抽樣誤差的影 響,可信性不強(qiáng),我們還需要進(jìn)行統(tǒng)計(jì)學(xué)檢驗(yàn).5.2 卡方檢驗(yàn)(2 X C)結(jié)果本研究中任一預(yù)測(cè)頻數(shù)均大于5,所以根據(jù)Chi-Square Tests表格分析各組的差異.SPSS輸出檢驗(yàn)結(jié)果如下：Chi-SquareValuedfAiymp, Sig, (2-sided)Pearson Chi-Square9.1 75d.010Like

32、lihood RatoLinear-by-Linear AssociationN of Valid CasesS 3367.7415021.C9,0C5日口 colls (0.0%)have expected count loss than 5. Pie minimum expected count is 24 67.卡方檢驗(yàn) (2 X C)結(jié)果顯福2=9.175 P = 0.010 ,說(shuō)明本研究中各組之間率的差值與 0的差異具有統(tǒng)計(jì)學(xué)意義,提示藥物干預(yù)與飲食、運(yùn)動(dòng)干預(yù)在降低受試者膽固醇濃度的作用 上存在不同.如果 P>0.05 ,那么就說(shuō)明各組之間率的差值與0的差異沒(méi)有統(tǒng)計(jì)學(xué)意義,即不

33、認(rèn)為各組之間存在差異.5.3 卡方檢驗(yàn)(2 X C)中的成比照擬分析SPSS如果卡方檢驗(yàn)2 X CP鮑.05 ,說(shuō)明至少有兩組之間的差異存在統(tǒng)計(jì)學(xué)意義.表格通過(guò)數(shù)字標(biāo)記提示了兩兩比擬的輸出的 risk_level * intervention Crosstabulation結(jié)果,如下標(biāo)注局部：riskjevel' irrieiveiilioii CrosstdbiilatioiiinterventionTotalDrugDietExerciserlsk_level HighCount1 Em23ib|30b74Expected Count24.724.724.774.0% within

34、 intervention32,0%66.0%0.0%492%Normal Count34a22t 120w76Expected Count25.325.325 37S.0% within intervention65.0%44.0%40.0%50.7%TotalCount505050150Expected Count50050 05 DO150.0% within intervention100.0%100 0%1CO.O%100.0%Each subscript letter denotes a subset of intervention cat&gories whose col

35、umn prcportions da not differ significantly from &ach other at the .05 l5vel.大家可能會(huì)注意到, 每組數(shù)據(jù)的標(biāo)記相同 即上下兩行的標(biāo)記相同, 那么我們只要知 道組間標(biāo)記的作用即可.dskjevel1 iiiterwiftion CrosstabuktioninterventionrugDietExerciseTotalrisk_JevwlHighCount29b30b74Expected Count24*24,74,0% wtthiln Intervention爰修56J>6CL.*49.3%Normal

36、Ccunt34i22b20b76Expected Count25 325325 376.Q% within intervention68.0%44.怖40.0%507%TotalCount505050160Expected Count50.050.05C 0150.0% wilhin intervention100.0%100 0%1GQ.D%100 0%Each subscript latter denotes a subset oTintarvention categories column proportions do not differ significantly from each

37、 other at the .05 level.表格的標(biāo)記是什么意思呢？第那么,risk_level * intervention Cross tabulation 種情況,各組間無(wú)差異,如下：1Nuntwf瑞 力*pand»ni,例*,. piF 八E Fl* i-*-"產(chǎn) ni<Wir3f CCnn pBr SUfraJGrcu01rtwip2Grtiup!3Group 45&AUp!61Groups 110 3 arc not staiistlca四但aae25upi 1 w * ore not neUitlC4 lyA-a.3Grou 彷 11&

38、; 5 nm noi Hti-rticaily寫(xiě)ign而ehAa-*-Add4Groups 1 tp B m膽 nd statistically significant司aa3a如上圖,各組間標(biāo)記一致,說(shuō)明各組之間無(wú)差異.第二種情況,任意兩組之間均存在差異,如下：Number otf Independent grou prgGroup 3b0nMjp 4Group 5ThefaHew ng pflMwiie coiRpaf MM ar«rfljit 前 3 iy 是 口可5 F® d 附.rmt： Groups 1r>d 2 CaB wrurt BbX Gign&am

39、p; 1 and 3 * frl-uSi *£*5. »d Group* 2 Md 3 (*b* Mr3g sTbc fdllow rig (Mjirwi 8戶二日后心門(mén)否立犍i s-W： stcaU/ s gn尸日二四 different； Groups 1 and 2(修" vartut "bl. &txi鼻 i 鼻M 3* .Ei隼 'c"i GOLip 耳 fliwi 4 fH1 d'l Groups 2 3M 3 fba SFUSi 17 G2UE 7and 4tr ¥*nus d"lr f

40、ind Grtiu健 3 And 4 CLviftut 'cn,T陋fM佻vg睇 6尸.酊40盧號(hào)赤岬stotfaty MgnUcDntfy dlffiewvt! Graug 1 ar*d 2 Co* versus 'bl. G3r 1 And 3 fa* VBFEUE *clr GpypE 1 4nd 4 fa* vrsu "<n. 匕gu蘆1 And 51 g值5后匕u瓶3and 3b,versus 口, Groups 2 and 4fcT versus *cf)L Groups 2 and 與(*"3 " veraus *e*)t G3

41、p& 3 and 4 re" versus F： ard Groups A and 5tf" rersu&即每組標(biāo)記字母均不相同,說(shuō)明任意兩組之間的差異均存在統(tǒng)計(jì)學(xué)意義.第三種情況, 有些組之間存在差異,而另一些組之間的差異沒(méi)有統(tǒng)計(jì)學(xué)意義,如下：hiufflfeef of haependem groupsGour I GroupIThorv li i mVctt y agnifte3nt 白粗陶口口.m orafUDrUonsi buiwwn Grtoup 1 and Gray.bbb2 f* wujk 匕"14i d G<oud i *nc

42、 Grgup 3'"TtufTb) but thur« * M,3過(guò)*叫Sign兩的E% dfiffotnet! ；H acigrii白de betwt4n GMg ? *才0 3簟 var$u4-,Hlhgre 姆 « 的v agntlfnt 0Wren« 翻 oropgnfonE betwen Grgp I and Grw 口a國(guó)內(nèi) b3看" grfui .口* bu! IZrir 荏 g M曲司C*lly 新gftf色/.中浦 口bciYErfc Gn&ups 1 and 2 fa-v*rfts "a" anc 0白口匹 2 and 3 fb" versus 'bl,BTh0 詬 愴 a cfiallEticati