/*-------------------------------------------------------------- * * SAS/STAT TEST LIBRARY * * NAME: calis13 * SUPPORT: Wolfgang M. Hartmann * UPDATE: * REFERENCE: Ability and Aspiration, LISREL VI (1985, p.III.5) * Data of CALSYN & KENNY (1977) * EVALUATION: * FUNCTION: First Order Confirmatory FA model. * parameter specification * initial estimates * maximum-likelihood estimates * R-squared values * coefficient of determination * goodness-of-fit measures * standard errors and t-values * variances and covariances * modification indices * MISC: * --------------------------------------------------------------*/ options ls=120 ps=60; title 'Ability and Aspiration, LISREL VI, p. III.5'; title2 'Data of CALSYN & KENNY (1977)'; data calken(TYPE=CORR); _TYPE_ = 'CORR'; input _NAME_ $ V1-V6; label V1='Self-concept of ability' V2='Perceived parental evaluation' V3='Perceived teacher evaluation' V4='Perceived friends evaluation' V5='Educational aspiration' V6='College plans'; datalines; V1 1. . . . . . V2 .73 1. . . . . V3 .70 .68 1. . . . V4 .58 .61 .57 1. . . V5 .46 .43 .40 .37 1. . V6 .56 .52 .48 .41 .72 1. ; proc calis data=calken method=max tech=nr edf=555 short mod pde; FACTOR n=2; MATRIX _F_ /* loadings */ [ ,1] = lam1-lam4 , /* factor 1 */ [ ,2] = 4 * 0 lam5 lam6 ; /* factor 2 */ MATRIX _P_ [1,1] = 2 * 1. , [1,2] = COR; /* factor correlation */ run; /* Alternative way to specify the same model */ /* using linear equations proc calis data=calken method=max tech=lm edf=555 all pde; LINEQS V1 = lam1 F1 + E1 , V2 = lam2 F1 + E2 , V3 = lam3 F1 + E3 , V4 = lam4 F1 + E4 , V5 = lam5 F2 + E5 , V6 = lam6 F2 + E6 ; STD E1-E6 = EPS: , F1-F2 = 2 * 1. ; COV F1 F2 = COR ; run; */