Replication character = R

Replication of observations in the data can be specified with R (or the specified character).

 

Replication character = R or one of A-Z # $ % &

Upper and lower case characters are the same. Other characters may be available. If you need to use one, please try it. More than one character is also allowed: Replication character = R#

There is no character between this and the number of replications (integer R6 or decimal R3.5).

 

Example 1: player 1 won 3 times against player 2, and lost 4 times:
Replication character = R ; this is the default value
R3 1 2 1  ; R3 "replicate this observation 3 times"
R4 1 2 0

 

Example 2: Roger won 3 times against Alfred, and lost 4 times:
Facets = 2 ; 2 facets in the data
Entered = 1, 1 ; both facets in the data are facet 1 in the labels
Models = ?,-?,D ; any element in facet 1 - any facet in element 1 -> dichotomous observation
Labels=
1, players
1 = Roger
2 = Alfred
...
*
Delements = LN ; element identifiers in the data are labels
Replication = # ; the replication character is # and we use R for the first letter of some element labels in the data.
Data=
#3 Roger Alfred 1
#4 Roger Alfred 0

 

Example 3: For one element, the data looks like 2.7, 5.6, 8.9, ranging from 0 to 10. but other items are integers.
In Facets, every advancing score must mean one higher level of the latent variable. In your data, 0,1,2,3,4,5,6,7,8,9,10  are 11 levels of performance. What does 2.7 mean?  From the viewpoint of Facets it means:
an observation of 2 weighted 0.3 (= 0.6) + an observation of 3 weighted 0.7 (= 2.1 so that 0.6+2.1=2.7)
so, if the original Facets observation was:
facet1, facet2, facet3, 2.7
then the Facets data is:
Data=
R0.3, facet1, facet2, facet3, 2
R0.7, facet1, facet2, facet3, 3

 

 

 

 

 


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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 Winsteps & Facets Events
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
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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