LISREL做CFA、模型及修正,手把手教會(huì)你

1、運(yùn)行 LISEREL Windows Application協(xié)方差檢驗(yàn)File t Import External Data in Other Formats （導(dǎo)入外部數(shù)據(jù)） 宀右擊任一變量名， 選擇 Define Variables （定義變量），點(diǎn)擊 Variable Type （設(shè)定變量類型），選擇Continuous （連續(xù)型）和Apply to all （應(yīng)用到所有），點(diǎn)擊OK、0K。如下圖所示：丨 EFFE2EFFE3EFFE4SPEE1SPEE2SPEE3MAR0030Q0JO10JOJO JO in m30DJO030ID0030105 0002.0005 0004.005.

2、0003.0003.000v nnn4000 2000 5.000 nnnB.0（ Define Variables4.020KoToTo1.0204.0405.0To5.0507.6:EFFE3EFFE4SFEE1SFEE2SPEE3HAKK1 llAKKMAW HUAIFINA2outtt5.0001.0005.0003.000<0003.00040002.0006.00040002.0005.0003 0005 OOu3.0001 nnn2.0006 0003.0006 000-1.0006.0003.000jOOO2.0007.000<000e nnn6.000f nnn3

3、.000To itltct more thwa time, hold dawn the CTHL key while cli ckin.g on the vari ables to be3 0004.000BJ000b.UUU5.000b.UUU6.000完成上述操作后點(diǎn)擊 save保存數(shù)據(jù)（注意數(shù)據(jù)應(yīng)保存在系統(tǒng)盤，否則可能得不出結(jié)果）Q龐13 S 11洌IS E ffiEFFE4SPEElSPEE2_ 10005000i.oool2000二 1 000r2.000p5000r5000r5.0004000r3ooo3.000finrin4 nnnsnnnData Tr arts form at

4、 i on StatisticsGraphsMultileviStatisticst output options.（輸出選項(xiàng)，選擇 Save to fi.、LISREL system data、Save the transformed data to.。輸入與之前文件名一致名字的cov、dsf文件（如下圖中test1.cov、test1.dsf）, Covariances :協(xié)方差）OutputMan ent Matrix叼 Save to fi p LISEEL system datSav to fil電：得到協(xié)方差矩陣接下來進(jìn)行CFAFlie t New 宀 Path Diagram 宀

5、保存（同名文件 testl.pth）Setup （定義相關(guān)設(shè)定）t Title and comments （般不用定義）t選擇next, 至 Group names（一般也不用定義）t next至Labels，如下圖（左側(cè) Observed Variables:觀測(cè)變量即觀測(cè)指 標(biāo)；右側(cè) Late nt Variables :潛變量）t選擇 Add/Read variables（得下圖，在 Add/Read variables 中選擇 PRELIS System Flie ）Labels1m i2VAR 2Observed VariablesAdd/Read VariablesLatent V

6、ariablesAdd Latent VariablesMovft UpFfl&vfi UphasPressoFresz bgeit t選擇 Browse.宀打開 testl.psfOK選擇Add late nt Variables （添加潛變量，手輸），如下圖Haig1EFFE12IFFE23IFFI34IFFE4SSFEE16SFEE27SPEE33MAKlaUAT>imObserved VariablesAid/Read VariiblesNameLatent VariablesAdd Latent VariablesPress the Down Arrow bn type

7、d in the prePress the Insert keyAdd one or li st of var i abl&s h&re （色” g.IeffeOKCancel得到點(diǎn)擊 next 進(jìn)入 Data （Statistics 中選擇 Covariances. File 中選擇 External ASCII Data , FileBrowse.中選擇同名 cov文件，Number of中輸入樣本數(shù)量）DataGroups:Summary statistFileMean included in the dataSwim ary Hatrix|Covar i ancesEx

8、ternal ASCII DataTFull matr Fortran for mitt FileBrewst.|C: Dio cum en t s and Se ttinsVjfStatisticsWeightInclude wei ma-1Nwnb電r ofMatrix to LeCovwr i aiLcesC Frevi oils點(diǎn)擊OK作圖'Groups：ZJModels：X-ModelObservedEFFE1EFFE2.ooEFFE3EFFE4SPEE10. 00SPEE2兀F1NAI0. 000. 000. 00F1NA2FINA3一 o口0000oi. ao0. 000

9、,00._0.00_ . 000.00LatentEFFESPEFMARKF NAEFFE1EFFE2EFFE3EFFE4SPEE1SPEE2SPEE3MARK1 MARKSMARK3FINA1FINA2FINA3廠o.aoSPEEMAPK1J口MARK2Y0. MARKS0.ooHAFF：Setups Build LISREL Syntax0.00FIMAt選擇estimates （估計(jì)值）Soluti on注：對(duì)于Standardized Solution值的刪減標(biāo)準(zhǔn)無一定說法，但一般應(yīng)當(dāng)高于 觀測(cè)指標(biāo)不多，可適當(dāng)降低標(biāo)準(zhǔn)。一般最少也應(yīng)大于0.5。上圖中對(duì)于較小的中: Standardiz

10、ed0.6、0.7。如果0.34應(yīng)刪除這條路徑，刪除后再運(yùn)行程序一次。如果有多條路徑要?jiǎng)h除，應(yīng)當(dāng)一條一條刪。完成刪減路徑工作后，查看模型擬合系數(shù)Output t Fit in dices （擬合指數(shù)），如下圖:=二二Degrees of Freedon = 50fllinumini F辻 Function Chi-Square = 218. 75 (P = 0. 0)Normal Theory Weighted Least Squares 匚hiSquare = 217. 77 (P = CL 0)Estimated Non-centralxty Parameter (NCP) = 157,7

11、790 Percent Confidence Interval for NCP 二(116. 43 : 206* 70)Minimum Fit Function Value = 0* 71Population Discrepancy Funct ion Value CFO) = CL 5190 Percent Confidence Interval for FO = (0.38 ; 0.67)Root Mean Square Error of Approximation (RMSEA) = 0» 092SO Percent Confidence Interval for RMSEA

12、= (0. 07S : CL 11)P-Value for Test of Close Fit (RMSEA < 0.05)二 C, 00Expected Cross-Validation Index CECVI) = 0.919D Percent Confidence Interval for ECVI = (0. 77 : L OT)EC¥I for Saturated Model 二 0. 59ECVI for Indepertdence Model = 6. 60Chi-Square for Independence Model with 78 Degress of F

13、reedom = 2005. 34Ind ep ends nee AIC = 203L 84Fodel AIC 二 279,77Saturat ed AIC = 182. 00Independence CAIC = 2023.38Model CAIC = 426,51Saturated CAIC = 612. ?3Norined Fit Index (NFI) = D* 89Non-Nocmed Fit Indeu (IfflFI) = 0. E9Parsimony Normed Fit Indes (PNFI)二 CL 69Comparative Fit Index (CFI)二 0. 92

14、Increment al Fit Index (IFI) = 0.92Relative Fit Index (RFI) - 0.83Critical N (CN) = 125,44Root Mean Square Residual (RHR) = 0.11St aridairdized RHR = 0. 083Goodness of Fit Index (GFI)二 0. 60Adjusted Gocdness of Fit Index (AGFI) = 0.85ParsiJhony Goodness of Fit Index CPGFI) = (L 59彳"semi擬合指標(biāo)建議值擬

15、合指標(biāo) 2df GH AGFI NFI IFI CFI RMR RMSEA P>0.9>0,9【 <0.05<0,08>0.05以上CFA完成接下來結(jié)構(gòu)方程模型分析Filet newi選擇 Path Diagram，如下圖USREL Windows AppficationAle View H1 創(chuàng) |P |1 AJ*la|倒倒創(chuàng)保存為test2.pthSetup （定義相關(guān)設(shè)定Title and comments （般不用定義選擇next, 至 Group names（一般也不用定義next至Labels，如下圖（左側(cè) Observed Variables:觀測(cè)變

16、量即觀測(cè)指 標(biāo)；右側(cè) Late nt Variables :潛變量）t選擇 Add/Read variables（得下圖，在 Add/Read variables 中選擇 PRELIS System Flie ）Labels1m i2VAR 2Observed VariablesAdd/Read VariablesLatent VariablesAdd Latent VariablesMovft UpFfl&vfi UphasPressoFresz bgeit t選擇 Browse.宀打開 testl.psfOK選擇Add late nt Variables （添加潛變量，手輸），如下

17、圖Haig1EFFE12IFFE23IFFI34IFFE4SSFEE16SFEE27SPEE33MAKlaUAT>imObserved VariablesAid/Read VariiblesNameLatent VariablesAdd Latent VariablesPress the Down Arrow bn typed in the prePress the Insert keyAdd one or li st of var i abl&s h&re （色” g.IeffeOKCancel得到點(diǎn)擊 next 進(jìn)入 Data （Statistics 中選擇 Cova

18、riances. File 中選擇 External ASCII Data , FileBrowse.中選擇同名 cov文件，Number of中輸入樣本數(shù)量）點(diǎn)擊OK結(jié)構(gòu)方程模型的路徑系數(shù)圖綠色：外生潛變量；灰色：外生觀測(cè)變量（外生觀測(cè)指標(biāo)） 黃色：內(nèi)生潛變量；藍(lán)色：內(nèi)生觀測(cè)變量（內(nèi)生觀測(cè)指標(biāo)）Groups:Observed | Y|-EFFE1EFFE2EFFE3EFFE4SPEE1SPEE2SPEE3MARK1MARK2MARK3FINA1FINA2FINA3LateintEta |1EFFESPEEMARKXFl NA!r " Eta下選中轉(zhuǎn)化為內(nèi)生潛系統(tǒng)均默認(rèn)為外生變量，在

19、Y下選中，轉(zhuǎn)化為內(nèi)生觀測(cè)變量，在變量 作圖，與CFA 樣，得到下圖42MARKnut0812"11,031*2MARKFI Mir EstiZnds c«i選擇Estimate中modification in dices （修正系數(shù)，MI值：增加某條路徑所減少的卡方值，從 大的開始），用以增加路徑。但一定要有理論依據(jù)，一般不隨便增加。SPEE1HNA1其中，選擇Estimate中T-values，從最小的開始，用以刪路徑。一般T值的絕對(duì)值應(yīng)當(dāng)大于1.96，才說明顯著水平達(dá)到0.05，用一個(gè)*表示。另，大于2.58用*表示，大于 用*表示。$4ii c Mq4.h1IZi.D

20、D0.0D*<1.00C hi-Equare=191.9? t df=49 P-value-.00000,3. 4£4*8.65Ch±-3quare=191,97, =49,P-v*lue=0.00000, RNSEA=0,097o.op0.0DRMSEA=0.0970.OO*11.24ES.Ofi 22.03*0.000.0014.730.0D*-丄 C.57MARKSEFFE2MARK3MARK1SPEE2EFFE4FINA3EFFE1SPEE3FINA2MARK；EFFE2SPEE2FINA3MARK1FINA1MARK3EFFEISPEE3SPEEIEFFEI

21、Models;JEstimate：|T-v*luis巒模型修正1twine最小值R專家未注冊(cè)Ml最大值最終模型根據(jù)Ml值添加路徑（根據(jù)數(shù)值大?。焕碚撘罁?jù)），后運(yùn)行根據(jù)Ml值添加路徑（根據(jù)數(shù)值大??；理論依據(jù)），后運(yùn)行T值最小值開始用以刪路徑，Ml值最大值開始用以增加路徑。無論增、減路徑都得一條一條進(jìn)行。D . 40Chi-Square-195.53, dfs51, P-value-JOOODO, RMSEA-0.D960.74根據(jù)T值依次刪除兩條路徑后（在其中最好保存語(yǔ)法）得到下圖:17B»ic Modtl+Emmttfc-Stuidurdion根據(jù)Ml值添加路徑（根據(jù)數(shù)值大小；理論依

22、據(jù)），后運(yùn)行根據(jù)Ml值添加路徑（根據(jù)數(shù)值大小；理論依據(jù)），后運(yùn)行上圖表明 SPEE對(duì)MARK影響系數(shù)為 0.45，EFFE對(duì)FINA影響系數(shù)為 0.24。根據(jù)Ml值添加路徑（根據(jù)數(shù)值大??；理論依據(jù)），后運(yùn)行Chi-Square=103.22 f df=50,P-value=O.00000, RMSEA=0.093Fit IndicesQrl+F以上結(jié)構(gòu)修正完成，接下來輸出相關(guān)指標(biāo)數(shù)據(jù):ie ®utput Window HelpSIM PUS Outputsod.4USREL OutputsXSelected FrintoutCorr el at ion Matrix of Param

23、eter EsStmdardi zd.ResidutlEri f *n t> - * *、尸17 Total Effects and IndirectFsctcr-scores Kegr7 g t dar_di zed SolutjCompletely StMidardiz«d SoliTechni cal OutpuMi scellute ouE R鯉冒ult雪 (see SeeExcluding iModi fication InPrint ANumber of Decimals (0=8) in th電* Invoke F ath Di agtUlf i de選擇 Tot

24、al Effects and Indirect Effects （總體影響和間接影響）、Standardized solution 點(diǎn)擊Next，選擇下列指標(biāo)輸出點(diǎn)擊OKSetup運(yùn)行語(yǔ)法打開同名OUT文件，所有指標(biāo)數(shù)據(jù)可以看到。 例如：TINumber of Number oF Number oF Number oF Number oF Number oFInput Uariables 13 V - Uariabl5 6 K - Uariables 6ETfi - Uariables 2 KSI - Uariables 2 Obseruations 309表示所有輸入變量13個(gè)Y變量（外生觀

25、測(cè)變量）6個(gè)X變量（內(nèi)生觀測(cè)變量）6個(gè) 外生潛變量2個(gè)內(nèi)生潛變量2個(gè)樣本數(shù)309TICovariance MatrixMARK1JURK2 MARK3FINA1FIHA2FINA3MAEK11. 37MAEK20. 841. 26MAEK30.850. 66FINA10. 11-0. 01FINA20. 260. 24FINA30, 360. 14EFFE10,240. 26EFFE20- 190. 16EFFE40.430. 19SPEE1U.400. 34SPEE20.27D. 26SPEE30. 340. 26Covariance Matrix.31.231.2?.420,801, 26

26、28553314114223o.o,0.0.o-oeo>2777561CTJ111A -nVo.o.o.o,0,0,0.03522818222000o.o.obiobo-io.ob871930222330001 .o.o,0.o.o.o.EFFE1EFFE2EFFE4SFEE1SPEE2EFFE1L55EFFE21. 151. 57EFFE40.931. 151. 62SPEE10.360. 3S0.381.16SPEE20, 150190.250,580. 39SPEE3-0. 020. 060,310.430.48上圖表示輸入的協(xié)方差矩陣SPEE31.37Couariaince Ma

27、trix of ETfi and KSIMARKFI HAEFFESPEEMARK0.98FINfi0.270.96EFFE0.14Q,22SPEE0.U30.17fl-311,00上圖表示變量間的協(xié)方差矩陣Goodness of Fit StatisticsDegrees of Freedom = 50Minimum Fit Function Chi-Square = 1 S3. 41 (P = CL Cl)Normal Theory Weighted Least Squares 匚hi-Square = 183. 22 (P = CL D)Estiiaated Kon-centrality

28、 Parameter (NCP) = 133*2290 Percent Confidence Interval for NCP = (9G. 57 ; 17S. 45)Miriimujii Fit Funct ion Value = U 60Population Discrepancy Function Value (F0) = 0,4390 Percent Cnnfidence Interval for F0 二(0* 31 : IL E8)Root Mean Square Error of Approximation (RMSEA) = 0* 09390 Percent Confidenc

29、e Interval for RMSEA = (0.OTS ; 0. 11)F-Value for Test of Close Fit (RMSEA < 0.05) = 0.00Expected Cross-Validation Index CEC¥I) = 0.7890 Percent Confidence Interval for ECVI = (0.65 ; 0.92)ECVI for Saturated Model = 0. 51ECVI for Independence Model = 6. 25hi-Square for Independence Model ivith 66