SPSS專用統(tǒng)計(jì)術(shù)語(yǔ)

1、SPSS用統(tǒng)計(jì)術(shù)語(yǔ)1、X/dfx2(卡方檢驗(yàn))檢驗(yàn)方法和分解融合(DF)方法x2值(Chi-Square)為22.4601,自由度(chi-squaredf)為4,P值(Pr>Chi-Square)為0.00022、RMRLISREL、AMOS等結(jié)構(gòu)方程模型分析軟件，為什么我的Amos輸出中找不到RMR和GFI這一項(xiàng)內(nèi)容。(1)間距參數(shù)RSm與混合參數(shù)Rmr(c)稱為附加參數(shù)(2)表示殘差均方根，殘差是指樣本導(dǎo)出的方差協(xié)方差矩陣與模型隱含的方差協(xié)方差矩陣中對(duì)應(yīng)元素的差值，RMR的值越小，模型擬合越好。rTtAu«s十口3 . anu+ AjiaL*yis:Nu：“ fui G工

2、口國(guó)+ 7ai iable ?LumimLy:?diajiBttl finiundif4 Nr:"foi咂面£ t EsiiJiates' HiniJiiaatian+ PairviEC Faram?t?Model Fit' 三尺 cut Mr； TimeMuAcIFilCAHN口更里展卷.圖里ilSlSummavyNTAKDFTCMIN/DF109S03 2B5485,0001 6565<M,0000S32076 25S561,0003 701 ELII 口/,哲胡笑涅臼曲*SAmarJJn摘妾慨琵Group r.inr.tor 1HasplinrC

3、fiHf雨KFIIFITLIFIDeftalrholJJela2ri02,613,552300,757.7303alui抵di。Jell.r)OD1.0001.000Lndependeiiccmodel,000,000000,000.000ParauHAiylirasPRA7I0PCHDetajlt.Q.530.6333ahuat&dnode：,DDO,000.DOOInJcpcndciiccnwdcl1ODO,000.003NCP匕心dslNCPLOSOHI90Ljdavitmo4由ng.2St244238400.If5SarirftpdnoiR'000,000CigLidc

4、pcndcDccmodel25152561579.5721658,470FMNFkLLN從你的圖片看，你的模型擬合度不好。AmosdoesnotreportGFI,PGFI,AGFIandRMRwhenyouestimatemeansandintercepts.Thisisbecauseitisnotclearhowtoincorporatemeansandinterceptsintotheconventionalformulasforthesestatistics.Onepossibilityistocalculatethesestatisticsbasedontheobservedvari

5、ances/covariancesandthefitted(implied)variances/covariances,leavingthemeansandinterceptsoutofthefitmeasure.Thatwayofcomputingthestatisticscouldbeusefulandiscertainlydefensible.Itwouldmakeagreatdealofsenseinthosemodelswheremeansandinterceptsareestimatedbutnotconstrained.Ontheotherhand,formodelsthatco

6、nstrainmeansandinterceptsitisimportanttopayattentiontohowwellthemodelreproducesthemeansandintercepts,aswellasthevariances/covariances.Anotherapproachwouldbetogeneralizethedefinitionsofthosestatisticstosomehowincorporatefailuretofitmeansandintercepts.Sofar,aunique,obviouslycorrect,wayofdoingthishasno

7、tbeenproposed.Forthesereasons,thedesigndecisionwasmadenottoreportGFI,PGFI,AGFIandRMRwhenmeansandinterceptsareestimated.回頭去看你的"View"里的"AnalysisProperties”,aEstimatesmeansandintercepets”是被選中了的，把那個(gè)復(fù)選框去掉后，報(bào)表里就有RMR和GFI等指數(shù)啦。3、NFI（1）神經(jīng)纖維指數(shù)；（2）NormedFitIndex,正規(guī)指數(shù)，越接近于1,說(shuō)明擬合越好。本特勒一波內(nèi)特規(guī)范合指數(shù)（NFI

8、）;（3）NormedFitIndex,正規(guī)擬合指數(shù)4、rmsea近彳以誤差均方根，rootmeansquareerrorofapproximation，衡量模型協(xié)方差與數(shù)據(jù)協(xié)方差陣的差異大小，RMSFA越小越好。5、GFI擬合優(yōu)度指數(shù)goodnessoffitindex6、RFI相對(duì)擬合指數(shù)，（1）renalfunctionindex腎功能指數(shù)（2）RelativeFitIndex7、NNFI非本特內(nèi)-范內(nèi)特規(guī)范擬合指數(shù)，8、IFIIncrementalFitIndex,增量擬合指數(shù)9、AGFIadjustedGFI,調(diào)整擬合優(yōu)度指數(shù)10、TLITucker-LewisIndex指數(shù)，TLI

9、可能大于1或者小于1,但一月在01之間，越接近1模型越理想。11、CFIComparativeFitIndex,比較擬合指數(shù)TheconfirmatoryfatoranalysisshowedthatthefitindexesforX2/df=3.622,GFI=0.92,AGFI=0.91,NFI=0.89,NNFI=0.90,RMSEA=0.069,CFI=0.90,IFI=0.90.StrivingforhighgoalshadnosignificantcorrelationswithSCL-90、SDS、SASandSWLS,butwithSES（r=0.241,P<0.01）.

10、W：夜有驗(yàn)證性因素分析顯示擬合指數(shù)X2/df=3.622,GFI=0.92,AGFI=0.91,NFI=0.87,NNFI=0.90,RMSEA=0.069,CFI=0.90,IFI=0.90。追求高標(biāo)準(zhǔn)與SCL-90、SDS、SAS和SWLS等效標(biāo)不相關(guān)，與SES的相關(guān)為0.241（P<0.01）;信息標(biāo)準(zhǔn)指數(shù)ISI完全標(biāo)準(zhǔn)化解（MI）相對(duì)擬合指數(shù)（RFI）大于0.90,近似均方根殘差（RMSEA）小于0.08,則模型與數(shù)據(jù)的擬合程度很好。非范擬合指數(shù)（NNFI）為0.93,近似均方根誤差（RMSEA）為0.079。12個(gè)分測(cè)驗(yàn)的完全標(biāo)準(zhǔn)化解（MI）分別為與自由度df之比、近似誤差均方

11、根（RMSEA）、擬合優(yōu)度指數(shù)（goodnessoffitindex,GFI）本特勒一波內(nèi)特規(guī)范擬合指數(shù)（NFI）、近似誤差平方根（RMSEA）和信息標(biāo)準(zhǔn)指數(shù)等?？筛鶕?jù)用于驗(yàn)證的數(shù)據(jù)特征1.2009年7月7日.7?goodnessoffitindexNNFICFI?df=,p（p+1）/2.（CFI）=0.95IncrementalFitIndex（IFI）=0.95RelativeFitIndex（RFI）=0.88.運(yùn)行l(wèi)isrel會(huì)產(chǎn)生一個(gè)GF文件，就是模型擬合指標(biāo)的文件，內(nèi)容如下（文件中是居中設(shè)置的）：DegreesofFreedom=35MinimumFitFunctionChi-S

12、quare=47.95(P=0.071)NormalTheoryWeightedLeastSquaresChi-Square=47.07(P=0.083)EstimatedNon-centralityParameter(NCP)=12.0790PercentConfidenceIntervalforNCP=(0.0;34.10)MinimumFitFunctionValue=0.048PopulationDiscrepancyFunctionValue(F0)=0.01290PercentConfidenceIntervalforF0=(0.0;0.034)RootMeanSquareErro

13、rofApproximation(RMSEA)=0.01990PercentConfidenceIntervalforRMSEA=(0.0;0.031)P-ValueforTestofCloseFit(RMSEA<0.05)=1.00ExpectedCross-ValidationIndex(ECVI)=0.08790PercentConfidenceIntervalforECVI=(0.075;0.11)ECVIforSaturatedModel=0.11ECVIforIndependenceModel=1.87Chi-SquareforIndependenceModelwith45D

14、egreesofFreedom=1843.25IndependenceAIC=1863.25ModelAIC=87.07SaturatedAIC=110.00IndependenceCAIC=1922.33ModelCAIC=205.23SaturatedCAIC=434.93NormedFitIndex(NFI)=0.97Non-NormedFitIndex(NNFI)=0.99ParsimonyNormedFitIndex(PNFI)=0.76ComparativeFitIndex(CFI)=0.99IncrementalFitIndex(IFI)=0.99RelativeFitIndex

15、(RFI)=0.97CriticalN(CN)=1195.65RootMeanSquareResidual(RMR)=0.049StandardizedRMR=0.021GoodnessofFitIndex(GFI)=0.99AdjustedGoodnessofFitIndex(AGFI)=0.99ParsimonyGoodnessofFitIndex(PGFI)=0.63txt 文件，并于首行指明擬合as.numeric() 轉(zhuǎn)成數(shù)值。細(xì)我現(xiàn)在想要做的是從多個(gè)這樣的文件中抽取特定的擬合指標(biāo)的值另存為一個(gè)指標(biāo)的名稱？在R在能否實(shí)現(xiàn)呢？該如何操作？能。因?yàn)檫@個(gè)文件的規(guī)律很明確。用readLine

16、s()讀進(jìn)來(lái)，用split()拆分'='，節(jié)我就不說(shuō)了，里面有幾行和其它行的規(guī)律不完全一樣。用兩行文本舉個(gè)例子吧，比如我現(xiàn)在讀了兩行文本放在x中：>x1 "P-ValueforTestofCloseFit(RMSEA<0.05)=1.00"2 "ExpectedCross-ValidationIndex(ECVI)=0.087"用'='為拆分符號(hào)把x拆掉：>strsplit(x,'=')11 "P-ValueforTestofCloseFit(RMSEA<0.05)"2 "1.00