Estimation Progress

This is for 32-bit Facets 3.87. Here is Help for 64-bit Facets 4

Once Facets has the needed information, it proceeds with constructing measures:

 

Facets top of screen output

 

The first part reports which files are being read and written.

are the quick-action buttons.

 

>........< is the iteration bar which indicates progress in processing the specification file.

 

Facets Table 1 screen output

 

Table 1 summarizes key aspects of the specifications.

How many facets? - The number of different facets that combine together to produce the observations.

How many elements? - The number of different elements found in each facet.

Compare these numbers with what you expect in order to verify that the specifications are correct.

 

Facets Table 2 screen output

 

Table 2 reports on the data. Here there are 1152 observations, and all have been matched to the specified labels and the specified measurement model.

 

Facets Table 3 screen output

 

Table 3 reports on the estimation of measures. The first estimation method used is PROX, the Normal Approximation algorithm, see "Rating Scale Analysis". The important consideration is that the "max.=" amount gets closer to zero.

 

At the same time, the data is checked for connectedness. Here "Subset connection O.K." is reported, so there is complete connectedness. If there is not, see Connectedness.

 

Facets screen iteration output

 

Estimation continues iteratively with JMLE, "joint maximum likelihood estimation", also known as UCON , "unconditional maximum likelihood", algorithm. This includes the Facets implementation of PMLE. "max. = .0914" at the bottom of this Figure means that the worst estimated measure predicts a raw score only .09 score points away from that observed. "max = -.0004" means that the biggest change in an estimate during this iteration is only .0004 logits. Since logits are only reported to 2 decimal places, this change is really meaningless. In this analysis, the convergence criteria appear to have been set more tightly than necessary, (but this is typical with high stakes examinations.) See also "My analysis does not converge."

 

When the convergence criteria are satisfied, estimation ceases. Or, to stop estimation more quickly, press Ctrl+F or select "Finish Iterating" on the Files pull-down menu.

 


Help for Facets Rasch Measurement and Rasch Analysis Software: www.winsteps.com Author: John Michael Linacre.
 

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Rasch Books and Publications
Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, 2nd Edn, 2024 George Engelhard, Jr. & Jue Wang Applying the Rasch Model (Winsteps, Facets) 4th Ed., Bond, Yan, Heene Advances in Rasch Analyses in the Human Sciences (Winsteps, Facets) 1st Ed., Boone, Staver Advances in Applications of Rasch Measurement in Science Education, X. Liu & W. J. Boone Rasch Analysis in the Human Sciences (Winsteps) Boone, Staver, Yale
Introduction to Many-Facet Rasch Measurement (Facets), Thomas Eckes Statistical Analyses for Language Testers (Facets), Rita Green Invariant Measurement with Raters and Rating Scales: Rasch Models for Rater-Mediated Assessments (Facets), George Engelhard, Jr. & Stefanie Wind Aplicação do Modelo de Rasch (Português), de Bond, Trevor G., Fox, Christine M Appliquer le modèle de Rasch: Défis et pistes de solution (Winsteps) E. Dionne, S. Béland
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