Donde Esta Lisrel ? http://www.ssicentral.com / be forewarned: Lisrel is not Mac-friendly

1. DondeEstaLisrel? http://www.ssicentral.com/be forewarned: Lisrel is not Mac-friendly

3. You can download a “free 15 day trial edition” (the program has everything, but it goes “poof” in 2 weeks), or you can download a “free student edition” (which remains accessible forever but has truncated options, e.g., fewer variables are allowed, etc.):

4. Small Example to Play with… Lisrel Syntax for Path Model Title end w period. “da”=data, ni=#input vars, no=sample size, ma=cm says analyze the cov matr path example miniwoohoo. dani=5 no=100 ma=cm cm sy 2.0113 -0.0719 2.5384 1.1926 -1.2155 2.0738 1.2482 -0.4925 0.8035 2.0076 0.7615 -0.9282 0.3866 1.1610 1.9957 la q c v cs r se v cs r q c / mo ny=3 ne=3 nx=2 nk=2 lx=id,fi td=ze,fily=id,fite=ze,fi ph=st,fr be=fu,frga=fu,fr pa be 0 0 0 1 0 0 0 1 0 pa ga 1 1 1 0 0 1 pd ou “la” = labels, next line list your vars (ni of them). “se” = select, endogenous first, then exogenous. “mo”=model, nx=#xvars, nk=#ksi constructs/factors, lx=factor ldgs matrix, “fu,fr”=full, free, td=meas error, “di,fr”=diag,free “pa”=pattern, 0 means set fixed (to zero), 1 means estimate this parameter. “pd”= draw a path diagram for me. “ou”= output

5. Lisrel Notation relates ‘s to ‘s column goes to/ affects/causes row relates ‘s to other ‘s column goes to row • column goes to • (or “affects” or • “causes” row)

6. Lisrel Notation PSI (prediction/modeling) errors on eta’s: PHI (intercorrelations among the exogeneous constructs, ksi’s) η1 η2 η3 ξ1 ξ2 η1 ζ1 0 0 η2 0 ζ2 0 η3 0 0 ζ3 ξ1 1 φ ξ2 φ 1

7. Small Example to Play with… Lisrel Syntax for Path Model path example miniwoohoo. da ni=5 no=100 ma=cm cm sy 1.00000 -0.03183 1.00000 0.58395 -0.52975 1.00000 0.62116 -0.21818 0.39381 1.00000 0.38010 -0.41242 0.19005 0.58002 1.00000 la q c v cs r se v cs r q c / mony=3 ne=3 nx=2 nk=2 lx=id,fi td=ze,fily=id,fite=ze,fiph=st,fr be=fu,frga=fu,fr pa be 0 0 0 1 0 0 0 1 0 pa ga 1 1 1 0 0 1 ou

8. Path Model Key Output BETA v cs r -------- -------- -------- v - - - - - - cs 0.05 - - - - (0.10) 0.49 r - - 0.51 - - (0.08) 6.73 GAMMA q c -------- -------- v 0.57 -0.51 (0.06) (0.06) 8.95 -8.07 cs 0.59 - - (0.10) 6.13 r - - -0.30 (0.08) -3.93 Parameter estimate Standard error t-statistic Goodness of Fit Statistics Degrees of Freedom = 5 Minimum Fit Function Chi-Square = 29.77 (P = 0.00) Comparative Fit Index (CFI) = 0.86 Standardized RMR = 0.073

9. The Lisrel Model Measurement Model: Structural Model: Definitions: y is a vector of observed indicators of the dependent latent endogenous variables x is a vector of independent, or exogenous, variables Λy is the factor loadings of y on η Λx is the matrix of factor loadings of of x on ξ η is a vector of latent dependent, or endogenous constructs ξ is a vector of the independent latent variables, exogenous constructs ε is vector of measurement errors in y δ is vector of measurement errors in x Γ is a matrix of coefficients of the ξ’s on the η’s (the structural relationships) B is a matrix of coefficients of the η’s on η’s (the structural relationship) ζ is a vector of equation errors (random disturbances) trying to predict the endogenous guys η (the structural relationship errors)

10. Figure 3: Consumer Evaluation Relationships per Culture, per Marketplace Goods Services Cost Cost Value Value Latin America Service Serv Qual Continue Qual Continue Prod Product Easy Easy SalesRep SalesRep Cost Cost Value Value Northern Europe Serv Serv Qual Continue Qual Continue Prod Prod Easy Easy SalesRep SalesRep Iacobucci, Grisaffe, Duhachek and Marcati, “FAC-SEM: A Methodology for Modeling Factorial Structural Equations Models, Applied to Cross-Cultural and Cross-Industry Drivers of Customer Evaluations,” Journal of Service Research. Research also featured in, “Mapping the World of Customer Satisfaction,” Harvard Business Review.