Table 0.2 Convergence report

(controlled by LCONV=, RCONV=, CONVERGE=, MPROX=, MJMLE=, CUTLO=, CUTHI=)

 

Table 0.1 Analysis Identification

Table 0.2 Convergence report

Table 0.3 Control file

Table 0.4 Subset details

Table 0 is in the Report Output File in the Edit menu. In the Output Table menu, request it from Subtable, 0.

 

                             CONVERGENCE TABLE

 

+----------------------------------------------------------------------------+

|    PROX          ACTIVE COUNT       EXTREME 5 RANGE      MAX LOGIT CHANGE  |

| ITERATION   PUPILS  ACTS    CATS     PUPILS  ACTS       MEASURES  STRUCTURE|

|----------------------------------------------------------------------------|

|        1       76      25     3       3.59    1.62        3.1355    -.1229 |

|        2       74      12     3       4.03    1.90         .3862    -.5328 |

|        3       74      12     3       4.19    1.96         .1356    -.0783 |

WARNING: DATA ARE AMBIGUOUSLY CONNECTED INTO 6 SUBSETS. MEASURES ACROSS SUBSETS ARE NOT COMPARABLE

 see Connection Ambiguities

----------------------------------------------------------------------------|

|    JMLE     MAX SCORE   MAX LOGIT    LEAST CONVERGED     CATEGORY STRUCTURE|

| ITERATION   RESIDUAL*    CHANGE    PUPIL  ACT      CAT   RESIDUAL   CHANGE |

|----------------------------------------------------------------------------|

|       1        -2.04       .2562       7      5*      2       -.72    .0003|

+----------------------------------------------------------------------------+

Time for estimation: 0:0:0.166

 

The meanings of the columns are:

PROX   normal approximation algorithm - for quick initial estimates

ITERATION  number of times through your data to calculate estimates

 

ACTIVE COUNT number of parameters participating in the estimation process after elimination of deletions, and perfect (maximum possible) and zero (minimum possible) scores:

PERSONS person parameters

ITEMS  item parameters

CATS  rating scale categories - shows 2 for dichotomies

 

These counts may reduce because persons, items or categories may have been

1.deleted

2.dropped because they have no responses

3.dropped from standard estimation because they are unanchored and have extreme scores. These will be reported with Bayesian estimates.

 

EXTREME 5 RANGE

PERSONS The current estimate of the spread between the average measure of the top 5 persons and the average measure of the bottom 5 persons.

ITEMS The current estimate of the spread between the average measure of the top 5 items and the average measure of the bottom 5 items.

MAX LOGIT CHANGE

MEASURES maximum logit change in any person or item estimate. This i expected to decrease gradually until convergence, i.e., less than LCONV=.

STRUCTURE maximum logit change in any Andrich Threshold estimate - for your information - need not be as small as MEASURES.

 

JMLE   JMLE joint maximum likelihood estimation - for precise estimates

ITERATION  number of times through your data to calculate estimates

It is unusual for more than 100 iterations to be required

MAX SCORE RESIDUAL maximum score residual (difference between integral observed core and decimal expected score) for any person or item estimate - used to compare with RCONV=. This number is expected to decrease gradually until convergence acceptable.

*   indicates to which person or item the residual applies.

 

MAX LOGIT CHANGE maximum logit change in any person or item estimate - used to compare with LCONV=. This number is expected to decrease gradually until convergence is acceptable.

 

LEAST CONVERGED element numbers are reported for the person, item and category farthest from meeting the convergence criteria.

*   indicates whether the person or the item is farthest from convergence.

  the CAT (category) may not be related to the ITEM to its left. See Table 3.2 for details of unconverted categories.

 

CATEGORY RESIDUAL maximum count residual (difference between integral observed count and decimal expected count) for any response structure category - for your information. This number is expected to decrease gradually. Values less than 0.5 have no substantive meaning.

 

STRUCTURE CHANGE maximum logit change in any structure calibration (usually Rasch-Andrich Threshold). Not used to decide convergence, but only for your information. This number is expected to decrease gradually.

 

Look for scores and residuals in the last iteration to be close to 0,


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Rasch Publications
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
Rating Scale Analysis, Wright & Masters Introduction to Rasch Measurement, E. Smith & R. Smith Introduction to Many-Facet Rasch Measurement, Thomas Eckes Invariant Measurement with Raters and Rating Scales: Rasch Models for Rater-Mediated Assessments, George Engelhard, Jr. & Stefanie Wind Statistical Analyses for Language Testers, Rita Green
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
in Spanish: Análisis de Rasch para todos, Agustín Tristán Mediciones, Posicionamientos y Diagnósticos Competitivos, Juan Ramón Oreja Rodríguez
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Coming Rasch-related Events
Jan. 5 - Feb. 2, 2018, Fri.-Fri. On-line workshop: Practical Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com
Jan. 10-16, 2018, Wed.-Tues. In-person workshop: Advanced Course in Rasch Measurement Theory and the application of RUMM2030, Perth, Australia (D. Andrich), Announcement
Jan. 17-19, 2018, Wed.-Fri. Rasch Conference: Seventh International Conference on Probabilistic Models for Measurement, Matilda Bay Club, Perth, Australia, Website
Jan. 22-24, 2018, Mon-Wed. In-person workshop: Rasch Measurement for Everybody en español (A. Tristan, Winsteps), San Luis Potosi, Mexico. www.ieia.com.mx
April 10-12, 2018, Tues.-Thurs. Rasch Conference: IOMW, New York, NY, www.iomw.org
April 13-17, 2018, Fri.-Tues. AERA, New York, NY, www.aera.net
May 22 - 24, 2018, Tues.-Thur. EALTA 2018 pre-conference workshop (Introduction to Rasch measurement using WINSTEPS and FACETS, Thomas Eckes & Frank Weiss-Motz), https://ealta2018.testdaf.de
May 25 - June 22, 2018, Fri.-Fri. On-line workshop: Practical Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com
June 27 - 29, 2018, Wed.-Fri. Measurement at the Crossroads: History, philosophy and sociology of measurement, Paris, France., https://measurement2018.sciencesconf.org
June 29 - July 27, 2018, Fri.-Fri. On-line workshop: Practical Rasch Measurement - Further Topics (E. Smith, Winsteps), www.statistics.com
July 25 - July 27, 2018, Wed.-Fri. Pacific-Rim Objective Measurement Symposium (PROMS), (Preconference workshops July 23-24, 2018) Fudan University, Shanghai, China "Applying Rasch Measurement in Language Assessment and across the Human Sciences" www.promsociety.org
Aug. 10 - Sept. 7, 2018, Fri.-Fri. On-line workshop: Many-Facet Rasch Measurement (E. Smith, Facets), www.statistics.com
Sept. 3 - 6, 2018, Mon.-Thurs. IMEKO World Congress, Belfast, Northern Ireland www.imeko2018.org
Oct. 12 - Nov. 9, 2018, Fri.-Fri. On-line workshop: Practical Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com

 

 

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