MPLUS input programs for Samejima’s Graded Response Model estimation.

In this section we give the MPLUS 5.1 input programs to conduct FIML and CIFA estimation of Samejima's graded model. The data file for this example, 'ppo3.dat', comes from Maydeu-Olivares, A., Rodríguez-Fornells, A., Gómez-Benito, J. and D'Zurilla, T.J. (2000). It consists of 776 responses to the five items of the PPO scale of the Social Problem Solving Inventory-Revised (SPSI-R). The responses to the items have been tricotomized by collapsing categories 0 and 1, and 3 and 4.

The input files provided are:

1) FIML; logistic link function and unstandardized parameterization

2) CIFA-ULS; normal link function and unstandardized parameterization transformed to logistic metric

3) CIFA-ULS; normal link function and standardized parameterization transformed to logistic metric

Notice that in MPLUS, Alfa/Beta (unstandardized) parameterization is called Theta parameterization and Tau/Lambda (standardized) parameterization is called Delta parameterization.

FILE FIML.INP

TITLE: FIML;

! by default, a logistic link function is used

! by default, unstandardized parameters are used

DATA:

FILE IS ppo3.dat;

VARIABLE:

!This defines variables names

NAMES ARE y1-y5;

!This defines variables as categorical

CATEGORICAL ARE ALL;

ANALYSIS:

!This calls for Maximum Likelihood estimation

ESTIMATOR = ML;

MODEL:

!Factor loadings are free to be estimated

f1 BY y1-y5*;

!This sets latent trait variance

f1@1;

FILE CIFA_unstandardized.INP

TITLE: CIFA unstandardized parameterization;

! by default, a normal link function is used

DATA: FILE IS ppo3.dat;

VARIABLE:

!This defines variables names

NAMES ARE y1-y5;

!This defines variables

!as categorical

CATEGORICAL ARE ALL;

ANALYSIS:

!This calls for ULS

!estimator

ESTIMATOR = ULS;

TYPE = MEANSTRUCTURE;

!This line calls for

!alfa/beta unstandardized estimates

PARAMETERIZATION = THETA;

MODEL:

!Factor loadings are to be estimated

f1 BY y1-y5*;

!Latent trait variance is set to 1

f1@1;

!Latent response variance = D^2, to achieve logistic metric

! If no logistic metric is desired simply set at 1

8;

FILE CIFA_standardized.INP

TITLE: CIFA standardized

! by default, a normal link function is used

DATA: FILE IS ppo3.dat;

VARIABLE:

!This defines variables names

NAMES ARE y1-y5;

!This defines variables

!as categorical

CATEGORICAL ARE ALL;

ANALYSIS:

!This calls for ULS estimation

ESTIMATOR = ULSMV;

TYPE = MEANSTRUCTURE;

!This calls for tau/lambda standardized estimates

PARAMETERIZATION = DELTA;

MODEL:

!Factor loadings free to be estimated

f1 BY y1-y5*.5(lambda1-lambda5);

!Factor variance is set to be 1

f1@1;

!Thresholds free to be estimated

[y1$1-y5$2*](tau1-tau10);

! No further commands are needed

! The next commands are optional. Given the estimated

! standardized parameters in normal metric, they

! are transformed to unstandardized estimates in

! logistic metric

! Mplus also prints SEs for the transformed parameters

MODEL CONSTRAINT:

NEW(beta1-beta5 alfa1-alfa10);

!Lambda to beta reparameterization

beta1 = 1.702*lambda1/SQRT(1-lambda1**2);

beta2 = 1.702*lambda2/SQRT(1-lambda2**2);

beta3 = 1.702*lambda3/SQRT(1-lambda3**2);

beta4 = 1.702*lambda4/SQRT(1-lambda4**2);

beta5 = 1.702*lambda5/SQRT(1-lambda5**2);

!tau to alpha reparameterization

alfa1 =1.702*tau1/SQRT(1-lambda1**2);

alfa2 =1.702*tau2/SQRT(1-lambda1**2);

alfa3 =1.702*tau3/SQRT(1-lambda2**2);

alfa4 =1.702*tau4/SQRT(1-lambda2**2);

alfa5 =1.702*tau5/SQRT(1-lambda3**2);

alfa6 =1.702*tau6/SQRT(1-lambda3**2);

alfa7 =1.702*tau7/SQRT(1-lambda4**2);

alfa8 =1.702*tau8/SQRT(1-lambda4**2);

alfa9 =1.702*tau9/SQRT(1-lambda5**2);

alfa10 =1.702*tau10/SQRT(1-lambda5**2);