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2008,40(9):10301040ActaPsychologicaSinicaDOI:10.3724/SP.J.1041.2008.010301030:2007-10-0932007-2008:,E2mail:sunxiaomin@bnu.edu.cn,:010-58802101Rasch312(1,,100875)(2KennedySchoolofGovernment,HarvardUniversity,MA02138,USA)Rasch,66,,,,FacetsFacets,,,Facets,Facets,;;RaschB841.711.1,,,[1],,[2]:,[3],Wagner:[4]:,:[5][6][5],,[7]1.2,,,,,,,,9:Rasch1031,,,,,,,,,(ClassicalTestTheory,CTT)(GeneralizabilityTheory,GT)CTT,,,CTT,,,CTT,Kendall,CTT,,KendallCTTGTCTT,,,GTCTT,CTT,,GT,(ItemResponseTheory,IRT),CTTGT,IRT,IRT,IRT,()CTT,IRT,IRT,IRT,IRTRaschRaschRaschlogPni1-Pni=Bn-DiPnini1-PniniBnn(n=1,2,,N)Dii(i=1,2,,L)Rasch,,,Rasch,,,,,Linacre[28]Rasch(ManyFacetsRaschModel,MFRM)MFRMRasch,RaschMFRM:logPnijkPnij(k-1)=Bn-Di-Cj-FkPnijknijkPnij(k-1)nijk-1Bnn(n=1,2,,N)Dii(i=1,2,,L)Cjj(j=1,2,,J)Fk(PartialCreditModel)k-1k(stepdifficul2ty),K(k=1,2,,K)logitsLogits,103240,MFRM,[10],MFRMMFRM,MFRM[11][1216][1719][20][21][2224],[25],,,MFRM,,CTT,MFRM,[26],JohnM.LinacreMFRMFacetsFacets(UnconditionalMaximumLikelihood)MFRMFacetsforWindows3.63.0[27]1.3Facets3.63.0,;,,MFRM,,22.17,,2131ABCDEFG34,1-342AEHIJKL32,35-662.2510:2.52.01.02.52.02.3IRTMFRM,FacetsforWindows3.63.033.1MFRMFacets3.63.0,6611,,123,,,[29]66-1.463.15logits,4.61logits,0.94(SE=112),53,3.15logits(SE=0.22);37,-1.46logits(SE=0.13)4infit(InfitMnSq),MFRM,fit,,MFRM,,,fitfit,MFRM,fit9:Rasch1033,fitfit0.51.5[13]0.81.2[14]infit112,,,infit0.8,1,3infit2.28,1.20,166S.E.InfitMnSqS.E.InfitMnSqS.E.InfitMnSq533.150.220.61191.570.181.05640.140.160.89233.050.211.44321.530.180.93400.130.160.99113.020.211.19621.470.190.96270.10.151.02252.840.210.63131.420.181630.060.160.84162.760.210.8311.40.181.055400.161.18612.690.211.05471.380.190.867-0.020.150.7732.670.212.28491.380.190.7744-0.020.160.8182.480.212.02451.350.190.9758-0.070.160.72482.310.210.71561.330.190.7860-0.170.151.05412.180.210.9421.330.180.6326-0.170.150.67292.170.21.32301.110.170.6446-0.180.151.75522.120.21.07330.870.170.965-0.240.150.86102.050.20.7440.80.161.156-0.490.141.1892.030.20.55360.690.170.8342-0.570.150.62141.980.191.72200.610.160.8866-0.650.151.23171.90.191.07220.590.161.5351-0.670.151.87241.90.190.94500.540.170.7528-0.840.140.69151.870.190.5390.520.171.2735-0.970.141.25311.850.190.61430.360.161.0838-0.990.140.52121.830.190.5180.360.161.0857-1.110.140.98651.780.21.02550.320.160.8559-1.140.140.54211.710.191.4340.230.150.837-1.460.130.780.940.170.991.20.020.36:RMSE(Model):0.18,AdjSD:1.19Separation:6.75,SeparationReliability:0.981RMSERootMean-SquareStandardError,(13)RMSEMSE(Mean2SquareStandardError),MSEAdj.SDAdj.SD(1101)MSESeparationAdj.SDRMSE,,Separation1.00.90,Separation3.0[30],Separa2tion6.75SeparationReliability,[26],,0;,11,SeparationReliability0.98,2,,2(65)=3236.4,p0.01,1034403.2,:,,2,,,Facets22FacetsMFRM(logits)MFRMMFRM(logits)MFRM183.5311.42743478.5490.23445283.7301.3332-23571.564-0.97622388.8102.67733682.4340.6936-2482.1350.83503769.866-1.46660575.157-0.245613873.460-0.9963-3672.361-0.495743981.5400.52400776.853-0.025124079.2450.1346-1888.8112.48834188.982.1810-2986.7132.0314-14275.755-0.5758-31086.6142.051314381.8390.3641-21190.833.02304479.146-0.0250-41285.8251.832054586221.3530-81383.1321.422664677.152-0.1855-31486.4151.981504785.7261.3829-31585.9231.871854888.992.31901689.262.76514985.9241.3828-41786.2201.91735082360.5439-31878.1510.364295175.256-0.6760-41984.8271.572345288.5122.121202079.8430.613765391.413.15102184.7291.712275478.947049-22279.6440.593865581.9370.3243-62389.443.05225686.4161.3331-152486.3171.9161577263-1.1164-12589.452.84415878.848-0.0752-42674.159-0.175455972.262-1.1465-32776.3540.14776078.350-0.1753-3287065-0.846146190.922.696-42986.3182.171176286.3191.4725-63082.8331.113306380.3410.0648-73186211.851926480.2420.1445-33284.8281.53244658971.7821-143381.8380.873446674.958-0.6559-12,1,66;2;3;4Facets;5;635,9:Rasch10352,,56,,16,Facets,31,1525,5656,Facets,3.3Facets,567,56,3356logitsModelS.E.A-0.358986.3-2.7-0.770.56E0.248683.8-2.2-0.510.51H-0.899088.3-1.7-0.540.57I0.238483.9-0.1-0.090.46J0.677881.83.80.750.4K-0.988988.5-0.5-0.140.56L-0.58586.91.90.60.4831;2;3;4;53,567,5,5,,56,66,12Facets3.4FacetsFacets,44,1;2,,,AE;4;51212,10.2629,2-0.2771,t=1.982,p=0.07112,0.054FacetsforWindows3.62.0,,infit103640Facets[26],,infit,Infit,MFRM,IRTCTT[31],,5656,,12Facets:,Facets:1,2,,,2561,3:567,5,5:,56;,5,Facets,,56,(1)11,1,212:,2660-0.17logits,78.374.1,42,21.6,66,,13,49:Rasch1037,,,,,2121,21,2,,:,,,,,,,,MFRM,5MFRM,66,:(1)MFRM,,(infit)(2),,FacetsFacets,,Facets,MFRM,,,MFRM1MaurerTJ,SolamonJM.Thescienceandpracticeofastructuredemploymentinterviewcoachingprogram.PersonnelPsychology,2006,59(2):4334562WiesnerWH,CronshawSF.Ameta-analyticinvestigationoftheimpactofinterviewformatanddegreeofstructureonthevalidityoftheemploymentinterview.JournalofOccupationalPsychology,1988,61(4):2752903SchmidtFL,ZimmermanRD.Acounterintuitivehypothesisaboutemploymentinterviewvalidityandsomesupportingevidence.JournalofAppliedPsychology,2004,89(3):5535614WaltersLC,MillerMR,ReeMJ.Structuredinterviewsforpilotselection:Noincrementalvalidity.InternationalJournalofAviati