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Análisis Factorial de Datos Categóricos

Análisis Factorial de Datos Categóricos. Item j. Por ejemplo: Capacidad para resolver ítems del tipo de los del ítem j. Distribución bivariada normal f(X * 1 ,X * 2 ). 3. 1,0. 1,1. -3. 3. 0,0. 0,1. -3. -3. 3. -3. 3. umbrales. CASO UNIDIMENSIONAL.

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Análisis Factorial de Datos Categóricos

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  1. Análisis Factorial de Datos Categóricos

  2. Item j Por ejemplo: Capacidad para resolver ítems del tipo de los del ítem j

  3. Distribución bivariada normal f(X*1,X*2) 3 1,0 1,1 -3 3 0,0 0,1 -3 -3 3 -3 3

  4. umbrales CASO UNIDIMENSIONAL Correlaciones policóricas observadas Correlaciones policóricas teóricas pesos El número de parámetros libres es el número de pesos más el número de umbrales

  5. THE MODEL ESTIMATION TERMINATED NORMALLY Chi-Square Test of Model Fit Value 941.111* Degrees of Freedom 85** P-Value 0.0000 * The chi-square value for MLM, MLMV, MLR, ULS, WLSM and WLSMV cannot be used for chi-square difference tests. MLM, MLR and WLSM chi-square difference testing is described in the Mplus Technical Appendices at www.statmodel.com. See chi-square difference testing in the index of the Mplus User's Guide. ** The degrees of freedom for MLMV, ULS and WLSMV are estimated according to a formula given in the Mplus Technical Appendices at www.statmodel.com. See degrees of freedom in the index of the Mplus User's Guide. CFI/TLI CFI 0.937 TLI 0.952 Number of Free Parameters 30 RMSEA (Root Mean Square Error Of Approximation) Estimate 0.038

  6. Estimates S.E. Est./S.E. F BY V1 0.433 0.022 19.662 V2 0.615 0.015 40.582 V3 0.388 0.016 24.648 V4 0.432 0.017 25.928 V5 0.453 0.016 27.865 V6 0.598 0.014 42.472 V7 0.535 0.014 37.142 V8 0.545 0.014 38.322 V9 0.454 0.018 25.645 V10 0.490 0.015 33.289 V11 0.622 0.013 46.666 V12 0.651 0.013 48.905 V13 0.620 0.013 47.435 V14 0.402 0.022 18.325 V15 0.581 0.014 41.530 Pesos estandarizados

  7. Estimates S.E. Est./S.E. Thresholds V1$1 -1.309 0.021 -62.833 V2$1 -0.742 0.017 -44.531 V3$1 -0.042 0.015 -2.788 V4$1 -0.650 0.016 -39.917 V5$1 0.581 0.016 36.237 V6$1 0.417 0.016 26.836 V7$1 -0.356 0.015 -23.096 V8$1 -0.172 0.015 -11.388 V9$1 -0.849 0.017 -49.319 V10$1 -0.023 0.015 -1.538 V11$1 0.077 0.015 5.119 V12$1 -0.442 0.016 -28.310 V13$1 -0.020 0.015 -1.322 V14$1 1.244 0.020 61.689 V15$1 0.331 0.015 21.544 Variances F 1.000 0.000 0.000

  8. TRI y AFC  X* DISTRIBUCION DE X* CONDICIONADA A LA PUNTUACIÓN EN EL FACTOR LATENTE: NORMAL CON MEDIA Y VARIANZA

  9. ¿Qué proporción de casos queda por debajo de en una distribución normal con media y varianza ? Aproximadamente… 

  10. TRI y AFC Simulamos los datos de 4000 personas en 10 ítems, según el L2P, con parámetros Comparamos los parámetros a y b con las estimaciones (de MULTILOG) y los valores de a y b recuperados, según

  11. AFC MULTILOG a b λτ v (e) a_re b_re a_es b_es

  12. M U L T ILOG Mplus

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