Initial estimates are obtained by the PROX algorithm, and then more refined ones by the JMLE (UCON) algorithm (or by the Facets implementation of PMLE). Check that convergence is occurring by reviewing the "Residual" and "Change" columns for smaller values each iteration. The iterative process can be terminated by pressing Ctrl+S simultaneously.
With T3onscreen= No, so that detailed output is displayed:
PROX - "normal approximation algorithm" is used to make initial estimates.
If "PROX Recount required" is displayed, some elements or categories had a 0 or perfect score. Measure for these can not be estimated directly, so their estimation is deferred and all marginal scores recounted without them. PROX ceases when the maximum change is less than 0.1 logits
JMLE= "joint maximum likelihood estimation" makes more precise estimates. The least-converged elements or rating-scale categories are shown (largest residual, largest residual percent, largest logit change). We want max.= to approach 0.
more JMLE iterations
JMLE ceases when the max.= values are small, and the convergence criteria are met. If the maximum residual does not decrease noticeably per iteration, then Estimation menu, "Bigger".. If the maximum residual oscillates between large positive and negative values, then Estimation menu "Reduce". See also "My analysis does not converge."
Column headings have the following meanings:
Facet = Name of the facet, as given in specifications or "Scale:" if details apply to a category of a rating scale (or partial credit).
Name = Name of element within Facet or model statement of a rating scale (or partial credit)
No./Cat = Number of element within facet or category number of a rating scale (or partial credit)
Raw = Raw score (= sum of categories, after renumbering if necessary), or count of responses in category, an integer
Expected = Score or count expected based on current estimates, in tenths
Residual = Difference between observed Score and Expected score, in tenths
Resd% = Residual/(Maximum score - minimum score)%.
Value = Revised estimate of parameter in log-odds units (logits) as a result of this iteration.
Change = Change in logit estimate from logit estimate of the previous iteration.
max.= is the maximum change or residual corresponding to any element, used to determine convergence.
Iteration = The number of times PROX or JMLE has been applied to the data.
Analysis fails after recounting
Table 3. Iteration Report
| Iteration Max. Score Residual Max. Logit Change |
| Elements % Categories Elements Steps |
Validating subset connection... (Subsets=No to bypass)
| PROX 1 Recount required 3.6889 |
Consolidating 2 subsets
Subset connection O.K.
| PROX 2 Recount required 2.3615 |
| PROX 3 Recount required 3.6142 |
| PROX 20 Recount required -20.4497 |
| PROX 21 Recount required -5.2877 |
Error F36: All data eliminated as extreme.
This report suggests that Models= does not match the data or that there are not enough observations to estimate the rating-scale structure.
Suggestion: specify a predefined rating-scale structure, such as Binomial Trials. For instance:
Models = ?, ?, B6 ; instead of R6
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|Rasch Measurement Transactions (free, online)||Rasch Measurement research papers (free, online)||Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch||Applying the Rasch Model 3rd. Ed., Bond & Fox||Best Test Design, Wright & Stone|
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|Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar||Journal of Applied Measurement||Rasch models for measurement, David Andrich||Constructing Measures, Mark Wilson||Rasch Analysis in the Human Sciences, Boone, Stave, Yale|
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