Table 20.1 Complete score-to-measure table on test of all items

For a score-to-measure table for fewer items, use ISELECT= or IDELETE= from the Specification Menu dialog box.

Table 20.2 Person score and measure distribution

Table 20.3 Complete score-to-calibration table for tests based on whole sample

 

                       TABLE OF MEASURES ON TEST OF 13 ITEM

----------------------------------------------------------------------------

| SCORE  MEASURE    S.E. | SCORE  MEASURE    S.E. | SCORE  MEASURE    S.E. |

|------------------------+------------------------+------------------------|

|    13    -6.34E   1.82 |    40    -1.35     .28 |    67     1.33     .35 |

|    14    -5.15     .99 |    41    -1.27     .28 |    68     1.46     .36 |

....

|    36    -1.65     .28 |    63      .84     .35 |    90     6.04    1.03 |

|    37    -1.58     .28 |    64      .96     .35 |    91     7.29E   1.84 |

|    38    -1.50     .28 |    65     1.08     .35 |                        |

|    39    -1.43     .28 |    66     1.21     .35 |                        |

----------------------------------------------------------------------------

CURRENT VALUES, UMEAN=.0000 USCALE=1.0000

TO SET MEASURE RANGE AS 0-100, UMEAN=46.5329 USCALE=7.3389

TO SET MEASURE RANGE TO MATCH RAW SCORE RANGE, UMEAN=49.2956 USCALE=5.7243

Predicting Score from Measure: Score = Measure * 8.2680 + 38.9511

Predicting Measure from Score: Measure = Score * .1158 + -4.5099

Maximum statistically different levels of performance (strata) = 3.8 

Wright's Sample-independent Person (Test) Reliability based on maximum strata = .94

 


 

TOTALSCORE= YES includes extreme (maximum possible score and minimum possible score) for example file: Exam1.txt

 

                       TABLE OF MEASURES ON TEST OF 18 TAP (includes 4 extreme items)

----------------------------------------------------------------------------

| SCORE  MEASURE    S.E. | SCORE  MEASURE    S.E. | SCORE  MEASURE    S.E. |

|------------------------+------------------------+------------------------|

|     0    -8.86E   1.90 |     7    -2.97     .81 |    14     3.75     .94 |

|     1    -8.11E   1.90 |     8    -2.27     .87 |    15     4.64     .97 |

|     2    -7.37E   1.89 |     9    -1.41     .99 |    16     5.72    1.16 |

|     3    -6.62E   1.88 |    10     -.28    1.11 |    17     7.14E   1.90 |

|     4    -5.26    1.11 |    11      .93    1.06 |    18     7.87E   1.92 |

|     5    -4.32     .88 |    12     1.95     .98 |                        |

|     6    -3.62     .81 |    13     2.87     .95 |                        |

----------------------------------------------------------------------------

 

TOTALSCORE= NO excludes extreme (maximum possible score and minimum possible score)  for example file: Exam1.txt

 

                       TABLE OF MEASURES ON TEST OF 14 NON-EXTREME TAP

----------------------------------------------------------------------------

| SCORE  MEASURE    S.E. | SCORE  MEASURE    S.E. | SCORE  MEASURE    S.E. |

|------------------------+------------------------+------------------------|

|     0    -6.62E   1.88 |     5    -2.27     .87 |    10     2.87     .95 |

|     1    -5.26    1.11 |     6    -1.41     .99 |    11     3.75     .94 |

|     2    -4.32     .88 |     7     -.28    1.11 |    12     4.64     .97 |

|     3    -3.62     .81 |     8      .93    1.06 |    13     5.72    1.16 |

|     4    -2.97     .81 |     9     1.95     .98 |    14     7.14E   1.90 |

----------------------------------------------------------------------------

 


 

 

In Table 20.1

Explanation

TABLE OF MEASURES ON TEST OF 13 ITEM

 

TOTALSCORE=Yes includes extreme items

TOTALSCORE=No excludes extreme items (if any)

Raw score-to-Measure Table for all raw scores on the complete set of all active non-extreme calibrated items. This can also be output with SCOREFILE=.

 

Table 20.1 shows the score-to-measure table for persons with complete data. For persons with missing data, this table does not apply.

 

Score-to-measure tables for subtests or persons with missing data can be produced by using ISELECT= or IDELETE= from the Specification menu before requesting Table 20.

 

If there are subsets, then the reported Table 20 is one of an infinite number of possible Table 20s.

SCORE

Raw score on the complete set of non-extreme or all items.  If IWEIGHT= produces decimal scores, then scores with one decimal place are shown. Some SCOREs may not be observable. Some observable scores may not be shown, but may be better approximated from TCCFILE=

MEASURE

Estimated measure for the SCORE raw score on all the items, adjusted by USCALE= and UIMEAN=, if active. The MEASURE may differ slightly from Table 17. Tighten convergence to make them agree exactly.

 

The SCOREFILE= and Table 20 person ability estimates are estimated on the basis that the current item difficulty estimates are the "true" estimates. These are the person estimates if you anchored (fixed) the items at their reported estimates. The convergence criterion used are LCONV= 0.01 and RCONV= 0.01 - these are considerably tighter than for the main analysis. So Table 20 is a more precise estimate of the person measures based on the final set of item difficulties.

 

PFILE=, Table 17 and the other Person Measure Tables show the person abilities that are the maximum likelihood estimates at the current stage of estimation. To make these two sets of estimates coincide, please tighten the convergence criteria in your Winsteps control file:

CONVERGE= L

LCONV=.0.001 ; or tighter

 

If STBIAS=YES is used, then score table measures are dependent on the data array, even if items are anchored.

-6.34E

"E" (Extreme, Extrapolated) is a warning that the accompanying value is not estimated in the usual way, but is an approximation based on arbitrary decisions. For extreme scores, the Rasch estimated would be infinite. So the arbitrary decision has been made to make the extreme score more central by the EXTREMESCORE= amount (or its default value), and to report the measure corresponding to that score. The Rasch standard error of an extreme score is also infinite, so the reported standard error of an "E" value is the standard error of the finite reported measure.

S.E.

The model-based standard error of the MEASURE, not adjusted for misfit.

CURRENT VALUES, UMEAN=.0000 USCALE=1.0000

This shows the current user-scaling. Changing the user-scaling in the Specification menu dialog box or the Help menu USCALE= calculator changes Table 20 immediately. Use this to experiment with different values of USCALE= and UIMEAN=.

TO SET MEASURE RANGE AS 0-100, UMEAN=46.5329 USCALE=7.3389

Suggested UIMEAN= and USCALE= values for transformation of the MEASUREs into user-friendly values in the range 0-100 resembling percentages.

TO SET MEASURE RANGE TO MATCH RAW SCORE RANGE, UMEAN=49.2956 USCALE=5.7243

Suggested UIMEAN= and USCALE= values for transformation of the MEASUREs into user-friendly values into the range or raw scores so that the  MEASUREs resemble raw scores.

Predicting Score from Measure: Score = Measure * 8.2680 + 38.9511

A linear approximation of the score-to-measure ogive useful for predicting raw scores on this set of items from measures. To approximate measures by raw scores: USCALE= 8.2680 and UIMEAN= 38.9511 <- use numbers from your Table 20.1

Predicting Measure from Score: Measure = Score * .1158 + -4.5099

A linear approximation of the score-to-measure ogive useful for predicting measures from raw scores on this set of items.

Maximum statistically different levels of performance (strata) = 3.8

Wright's Sample-independent Person (Test) Reliability based on maximum strata = 0.94

Across the raw-score range in Table 20.1, statistically significant different raw scores are 1.96 * (M1 - M2) / √(SE12 + SE22) apart where M1 and M2 are the two measures. SE1 and SE2 are their two standard errors. See www.rasch.org/rmt/rmt144k.htm. The number of different levels (strata) resembles a separation index. Wright's matching "Test" Reliability is shown. These are equivalent to the Separation and Reliability of a person sample with a uniform distribution having the range of the MEASUREs in Table 20.

 

                                1

PERSON            1  1123 55247311 6 35411272 12

                   T      S       M      S      T

%TILE             0    10 20 40 50 60 70 80 90 99

 

ITEM                       1  141221  1

                           T  S  M S  T

%TILE                      0 10 60 90 99

 

A graph of the score to measure conversion is also reported. '*' indicates the conversion. This is the Test Chracteristic Curve, TCC. Table 20.1 gives the score-to-measure conversion for a complete test, when going from the y-axis (score) to the x-axis (measure). When going from the x-axis (measure) to the y-axis(score), it predicts what score on the complete test is expected to be observed for any particular measure on the x-axis. For CAT tests and the like, no one takes the complete test, so going from the y-axis to the x-axis does not apply. But going from the x-axis to the y-axis predicts what the raw score on the complete bank would have been, i.e., the expected total score, if the whole bank had been administered.

 

Measure distributions for the persons and items are shown below the score-to-measure table. M is the mean, S is one P.SD (population standard deviation) from the mean. T is two P.SDs from the mean. %ILE is the percentile, the percentage below the measure. Percentiles have the range 0-99.

 


 

Test Information

 

 

 

The statistical information is (USCALE/S.E.)². These are plotted in the test information function in the Graph window. You can also plot the values reported in TCCFILE=

 


 

Score-to-measure Table 20 is to be produced from known item and rating scale structure difficulties

 

In your Winsteps control file:

IAFILE=if.txt ; usually values from IFILE=if.txt of another analysis  ; the item anchor file containing the known item difficulties

SAFILE=sf.txt ; usually values from SFILE=sf.txt of another analysis ; the structure/step anchor file (only for polytomies)

CONVERGE=L  ; only logit change is used for convergence

LCONV=0.0001  ; logit change too small to appear on any report.

STBIAS=NO  ; no estimation bias correction with anchor values

TFILE=*

20   ; the score table

*

 

The data file comprises two dummy data records, so that every item has a non extreme score, e.g.,

For dichotomies:

CODES = 01

Record 1: 10101010101

Record 2: 01010101010

 

For a rating scale from 1 to 5:

CODES = 12345

Record 1: 15151515151

Record 2: 51515151515


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

Facets Rasch measurement software. Buy for $149. & site licenses. Freeware student/evaluation Minifac download
Winsteps Rasch measurement software. Buy for $149. & site licenses. Freeware student/evaluation Ministep download

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
Exploring Rating Scale Functioning for Survey Research (R, Facets), Stefanie Wind Rasch Measurement: Applications, Khine Winsteps Tutorials - free
Facets Tutorials - free
Many-Facet Rasch Measurement (Facets) - free, J.M. Linacre Fairness, Justice and Language Assessment (Winsteps, Facets), McNamara, Knoch, Fan
Other Rasch-Related Resources: Rasch Measurement YouTube Channel
Rasch Measurement Transactions & Rasch Measurement research papers - free An Introduction to the Rasch Model with Examples in R (eRm, etc.), Debelak, Strobl, Zeigenfuse Rasch Measurement Theory Analysis in R, Wind, Hua Applying the Rasch Model in Social Sciences Using R, Lamprianou El modelo métrico de Rasch: Fundamentación, implementación e interpretación de la medida en ciencias sociales (Spanish Edition), Manuel González-Montesinos M.
Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch Rasch Models for Measurement, David Andrich Constructing Measures, Mark Wilson Best Test Design - free, Wright & Stone
Rating Scale Analysis - free, Wright & Masters
Virtual Standard Setting: Setting Cut Scores, Charalambos Kollias Diseño de Mejores Pruebas - free, Spanish Best Test Design A Course in Rasch Measurement Theory, Andrich, Marais Rasch Models in Health, Christensen, Kreiner, Mesba Multivariate and Mixture Distribution Rasch Models, von Davier, Carstensen
As an Amazon Associate I earn from qualifying purchases. This does not change what you pay.

facebook Forum: Rasch Measurement Forum to discuss any Rasch-related topic

To receive News Emails about Winsteps and Facets by subscribing to the Winsteps.com email list,
enter your email address here:

I want to Subscribe: & click below
I want to Unsubscribe: & click below

Please set your SPAM filter to accept emails from Winsteps.com
The Winsteps.com email list is only used to email information about Winsteps, Facets and associated Rasch Measurement activities. Your email address is not shared with third-parties. Every email sent from the list includes the option to unsubscribe.

Questions, Suggestions? Want to update Winsteps or Facets? Please email Mike Linacre, author of Winsteps mike@winsteps.com


State-of-the-art : single-user and site licenses : free student/evaluation versions : download immediately : instructional PDFs : user forum : assistance by email : bugs fixed fast : free update eligibility : backwards compatible : money back if not satisfied
 
Rasch, Winsteps, Facets online Tutorials


 

 

 

Our current URL is www.winsteps.com

Winsteps® is a registered trademark