LOGO One of the easiest to use Software: Winsteps www.winsteps.com.

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Presentation transcript:

LOGO One of the easiest to use Software: Winsteps

LOGO Introduction Developer of the program: John M. Linacre 1. Provides processing of data within Rasch analysis Tel/Fax: (312)

LOGO Key options of Winsteps  Test and item analysis Calibration of item difficulty Investigation of category functioning Discovering of dimensionality Construction of scale ability (item map) Construction of item characteristic curves and item information curves Differential Item Functioning analysis Analysis of polytomous response structures (rating scales and partial credit items) Fit statistics analysis etc.  Examinee analysis Analysis of responses of a examinees etc.

LOGO Work-flow with Winsteps Control fileData file WinstepsWinsteps GraphsOutput tablesReport Output File

LOGO How to make a control File?

LOGO The control file tells what analysis you want to do. The template file, TEMPLATE.TXT. gives you an outline to start from &INST ; optional TITLE = "Put your page heading here" ;Input Data Format NAME1 = 1 ; column of start of person information NAMLEN = 30 ; maximum length of person information ITEM1 = ? ; column of first item-level response NI = ?? ; number of items = test length XWIDE = 1 ; number of columns per response PERSON = Person ; Persons are called... ITEM = Item ; Items are called... ; DATA = ; data after control specifications

LOGO An example of a control file for dichotomous data &INST TITLE = "Biology-1.1" PERSON = Person ; persons are... ITEM = Item ; items are... ITEM1 = 2 ; column of response to first item in data record NI = 37 ; number of items NAME1 = 1 ; column of first character of person identifying label NAMELEN = 21 ; length of person label XWIDE = 1 ; number of columns per item response CODES = 01 ; valid codes in data file UIMEAN = 0 ; item mean for local origin USCALE = 1 ; user scaling for logits UDECIM = 2 ; reported decimal places for user scaling GROUPS=0 ; specify that each item has its own rating scale (partial credit) &END ;Put item labels here for NI= lines A1 A2 A3 A4 A5 … END LABELS …

LOGO An example of a control file for polytomous data (PCM) &INST TITLE="PCM" NAME1=1 XWIDE=1 ITEM1=11 NI=45 CODES= GROUPS=0 PERSON=PERSON ITEM=TASKS &END … END LABELS …..

LOGO An example of a control file for polytomous data (RSM) &INST TITLE="RSM" NAME1=1 XWIDE=1 ITEM1=11 NI=20 CODES=01234 NEWSCORE=12345 MODELS=R PERSON=PERSON ITEM=TASKS &END … END LABELS ……………………

LOGO The process is running…

LOGO Getting of outputs

LOGO An example of an output table (table 3.1 Summary statistics) TABLE 3.1 Русский язык ZOU287WS.TXT Mar 21 10: INPUT: 1464 Person 34 Item REPORTED: 1464 Person 34 Item 90 CATS WINSTEPS SUMMARY OF 1464 MEASURED Person | TOTAL MODEL INFIT OUTFIT | | SCORE COUNT MEASURE ERROR MNSQ ZSTD MNSQ ZSTD | | | | MEAN | | S.D | | MAX | | MIN | | | | REAL RMSE.36 TRUE SD.84 SEPARATION 2.33 Person RELIABILITY.84 | |MODEL RMSE.34 TRUE SD.85 SEPARATION 2.49 Person RELIABILITY.86 | | S.E. OF Person MEAN =.02 | VALID RESPONSES: 85.7% (APPROXIMATE) Person RAW SCORE-TO-MEASURE CORRELATION =.94 (approximate due to missing data) CRONBACH ALPHA (KR-20) Person RAW SCORE "TEST" RELIABILITY =.90 (approximate due to missing data) SUMMARY OF 34 MEASURED Item | TOTAL MODEL INFIT OUTFIT | | SCORE COUNT MEASURE ERROR MNSQ ZSTD MNSQ ZSTD | | | | MEAN | | S.D | | MAX | | MIN | | | Estimated person ability Fit statistics Error of measurement The number of responses made Number of correct responses including extreme scores Item calibration (difficulty) The average value of the statistic Sample standard deviation Information- weighted fit statistic Outlier-sensitive fit statistic

LOGO An example of output table (table 14.1 Item: entry) TABLE 14.1 Русский язык ZOU287WS.TXT Mar 21 10: INPUT: 1464 Person 34 Item REPORTED: 1464 Person 34 Item 90 CATS WINSTEPS Person: REAL SEP.: 2.33 REL.: Item: REAL SEP.: REL.: 1.00 Item STATISTICS: ENTRY ORDER |ENTRY TOTAL TOTAL MODEL| INFIT | OUTFIT |PT-MEASURE |EXACT MATCH| | |NUMBER SCORE COUNT MEASURE S.E. |MNSQ ZSTD|MNSQ ZSTD|CORR. EXP.| OBS% EXP%| Item G | | | | |1.00.1| |.38.38| | R04Q2_1 0 | | | | |.44.34| | R04Q2_2 0 | | | | |.52.50| | R04Q2_3 0 | | | | |.41.38| | R04Q2_4 0 | | | | |.51.38| | R04Q2_5 0 | | | | |.53.51| | R04Q2_6 0 | | | | |.41.38| | R04Q2_7 0 | | |1.01.2| |.47.48| | R04Q2_8 0 | … | | | |.19.43| | R04Q7_1 0 | | |1.02.7| |.36.37| | R04Q7_2 0 | | |1.01.4|1.00.0|.37.38| | R04Q7_3 0 | | | | |.35.48| | R04Q7_4 0 | | |1.01.3|1.01.2|.58.59| | R04Q7_5 0 | | | | MEAN | | | | | | | S.D | | | | | | the sum of the correct responses to an item by the persons the number of data points used to construct measures The item difficulty in logits The standard error for the estimate Standardized information- weighted mean square statistic Standardized outlier- sensitive mean square statistic Point-biserial correlation

LOGO An example of examinee responses (table 7.1 person: responses) Individual number Test score A number of responses with notes of significant deviations (* — significantly negative, + — significantly positive) Part А | Part В | Part С 101, ** * * * + 152, * * * * * * * * , ***** * NUMBER - NAME -- POSITION MEASURE - INFIT (MNSQ) OUTFIT RESPONSE: 1: Z-RESIDUAL: RESPONSE: 11: Z-RESIDUAL: -3 RESPONSE: 21: Z-RESIDUAL: -3 RESPONSE: 31: ………………………………………… Z-RESIDUAL: Individual number Significantly negative response Test score Fit statistics

LOGO Item map (table 12) TABLE 12.2 Русский язык ZOU000WS.TXT Mar 19 1: INPUT: 1464 Person 34 Item REPORTED: 1464 Person 34 Item 90 CATS WINSTEPS Person - MAP - Item | 4. + | | 2. T+.## |.# |.## |T R04Q1_8 R04Q1_9.### |.#### |.#### | R04Q7_4 1.####### S+ R04Q1_3.####### | R04Q7_5.####### |S R04Q1_5 R04Q8_8.####### | R04Q1_1 R04Q2_12 R04Q2_6.########### | R04Q1_2 R04Q1_4 R04Q1_7 R04Q8_4 ########## |.########### M| R04Q2_1 R04Q2_7 0.########## +M R04Q8_7.########### | R04Q7_3.######## | R04Q2_3 R04Q2_4 R04Q2_5.######## | R04Q7_2 R04Q8_2 ######## | R04Q7_1 R04Q8_3 R04Q8_6.##### |S R04Q8_5.##### S| R04Q2_10 R04Q2_8 R04Q8_1 -1.### + R04Q1_6 R04Q2_9.### | R04Q2_11 R04Q2_2.### |.## |.# |T.## T|. | -2.# +. | |. | -3 + | EACH "#" IS 9. EACH "." IS 1 TO 8 Logits Mean (examinees) Mean (items)

LOGO Graphs

LOGO Item characteristic curve Empirical data Model curve Confidence interval

LOGO Category Probability Curve Category “0” Category “1” Category “2”

LOGO Item Information Function Curve The biggest error of measurement The lowest error of measurement The biggest error of measurement

LOGO Test Information Function The biggest error of measurement The lowest error of measurement

LOGO +  Clear graphs and plots + confidence intervals for model and empirical item characteristic curves (the boundary lines which indicate upper and lower 95% two-sided confidence intervals)  A detailed and easy to use manual  Possibility of examinee responses analysis -  Provides only Rasch analysis, can not be used for 2Pl or 3Pl analysis Advantages and limitations of the program

LOGO