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Path Analysis SAS/ Calis

Path Analysis SAS/ Calis. Read in the Data. options formdlim ='-' nodate pagno =min; TITLE 'Path Analysis, Ingram Data' ; data Ingram(type= corr ); INPUT _TYPE_ $ _NAME_ $ Attitude SubNorm PBC Intent Behavior; CARDS;. N . 60 60 60 60 60

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Path Analysis SAS/ Calis

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  1. Path AnalysisSAS/Calis

  2. Read in the Data options formdlim='-' nodatepagno=min; TITLE 'Path Analysis, Ingram Data' ; data Ingram(type=corr); INPUT _TYPE_ $ _NAME_ $ Attitude SubNorm PBC Intent Behavior; CARDS;

  3. N . 60 60 60 60 60 MEAN . 32.02 45.71 40.25 16.92 43.92 STD . 6.96 12.32 7.62 3.83 16.66 CORR Attitude 1 .472 .665 .767 .525 CORR Subnorm .472 1 .505 .411 .379 CORR PBC .665 .505 1 .458 .496 CORR Intent .767 .411 .458 1 .503 CORR Behavior .525 .379 .496 .503 1

  4. Conduct the Analysis ProcCalis PRINT; • PRINT adds to the default output the total effects matrix (and some other things)

  5. Linear Equations LINEQS Intent = b1 Attitude + b2 SubNorm + b3 PBC + E1, • Intent has paths to it from Attitude, SubNorm, PBC, and E1 (the error term) • b1, b2, and b3 are the path coefficients that we want SAS to estimate for us

  6. Linear Equations Behavior = b4 Intent + b5 PBC + E2; • Behavior has paths to it from Intent, PBC, and E2. • SAS assumes that the exogenous variables (Attitude, SubNorm, and PBC) are correlated.

  7. Linear Equations STD e1-e2 = V1-V2; run; • The error terms be estimated as parameters V1 and V2.

  8. The Output • You will find much of the same output we found earlier with AMOS, but differently formatted. • I shall copy just a bit of it here.

  9. The Path Coefficients

  10. The Covariances

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