Transcript Winsteps

One of the easiest to use
Software: Winsteps
www.winsteps.com
LOGO
LOGO
Introduction
1.
Developer of the program: John M. Linacre
2.
Provides processing of data within Rasch
analysis
3.
www.winsteps.com
4.
Tel/Fax: (312)264-2352
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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.
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Work-flow with Winsteps
Control file
Data file
Winsteps
Report Output File
Output tables
Graphs
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How to make a control File?
The control file tells what analysis you want
to do. The template file, TEMPLATE.TXT.
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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
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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
11101111111111011011111110111111101111
21100000011110001111110001101111011110
…
An example of a control file for
polytomous data (PCM)
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&INST
TITLE="PCM"
NAME1=1
XWIDE=1
ITEM1=11
NI=45
CODES=012345
GROUPS=0
PERSON=PERSON
ITEM=TASKS
&END
…
END LABELS
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2
3
4
5
011000000100000000100110010001010100000010001
000000210021002100300211010120012200001010101
011001010101211410112210011222310100010122100
245401543342303353544534444344252232445255525
121001010221233201010210010000311300000022110
…..
An example of a control file for
polytomous data (RSM)
LOGO
&INST
TITLE="RSM"
NAME1=1
XWIDE=1
ITEM1=11
NI=20
CODES=01234
NEWSCORE=12345
MODELS=R
PERSON=PERSON
ITEM=TASKS
&END
…
END LABELS
1
2
3
4
5
01111201211011122101
24244323323342231123
21010401131301111200
00031200102100130212
11322222211201220
……………………
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The process is running…
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Getting of outputs
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An example of an output table (table 3.1
Summary statistics)
TABLE 3.1 Русский язык
ZOU287WS.TXT Mar 21 10:46 2012
INPUT: 1464 Person 34 Item REPORTED: 1464 Person 34 Item 90 CATS WINSTEPS 3.72.3
-----------------------------------------------------------------------------------number
of
The
responses made
Fit statistics
Estimated person ability
SUMMARY OF 1464 MEASURED Person
------------------------------------------------------------------------------|
TOTAL
MODEL
INFIT
OUTFIT
|
|
SCORE
COUNT
MEASURE
ERROR
MNSQ
ZSTD
MNSQ
ZSTD |
|-----------------------------------------------------------------------------|
Number of| MEAN
25.0
29.1
.12
.33
1.02
.1
1.01
.0 |
Error of
correct | S.D.
10.8
5.2
.92
.07
.27
1.0
.33
1.0 |
55.0
34.0
4.05
1.06
2.28
3.7
4.34
4.7 | measurement
responses| MAX.
|
MIN.
1.0
7.0
-2.88
.28
.44
-3.0
.34
-2.6
|
including
extreme |-----------------------------------------------------------------------------|
.36 TRUE SD
.84 SEPARATION 2.33 Person RELIABILITY .84 |
scores | REAL RMSE
|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)
InformationOutlier-sensitive
Item calibration
(difficulty)
weighted fit
fit statistic
The average SUMMARY OF 34 MEASURED Item
statistic
value of------------------------------------------------------------------------------the
statistic
|
TOTAL
MODEL
INFIT
OUTFIT
|
|
SCORE
COUNT
MEASURE
ERROR
MNSQ
ZSTD
MNSQ
ZSTD |
|-----------------------------------------------------------------------------|
| MEAN
1078.3
1255.1
.00
.05
1.00
-.2
1.01
-.1 |
Sample | S.D.
498.2
167.6
.77
.01
.10
2.7
.15
2.8 |
standard | MAX.
2173.0
1442.0
1.56
.07
1.39
9.9
1.67
9.9 |
deviation | MIN.
416.0
811.0
-1.20
.04
.88
-5.8
.82
-5.5 |
|-----------------------------------------------------------------------------|
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An example of output table
(table 14.1 Item: entry)
TABLE
ZOU287WS.TXT Mar 21 10:46 2012
the sum
of 14.1 Русский язык
INPUT: 1464 Person 34 Item REPORTED: 1464 Person 34 Item 90 CATS WINSTEPS 3.72.3
the correct
-----------------------------------------------------------------------------------responses
Person: REAL SEP.: 2.33 REL.: .84 ... Item: REAL SEP.: 14.45
REL.: 1.00
Standardized
outlierto an item
sensitive mean square
number
Item STATISTICS: the
ENTRY
ORDERof data points
by the
statistic
used to construct measures
persons
Point-biserial
correlation
------------------------------------------------------------------------------------------------|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
693
1431
.20
.06|1.00
.1|1.03
1.1| .38
.38| 66.0 66.0| R04Q2_1 0 |
|
2
1075
1431
-1.16
.07| .93 -2.2| .82 -3.6| .44
.34| 77.1 76.9| R04Q2_2 0 |
|
3
1673
1442
-.25
.04| .99
-.3| .98
-.6| .52
.50| 54.7 51.9| R04Q2_3 0 |
|
4
850
1425
-.33
.06| .97 -1.4| .94 -1.8| .41
.38| 68.2 67.7| R04Q2_4 0 |
|
5
822
1371
-.30
.06|
.88
-5.8|
.83
-5.5|
.51
.38| 73.0 67.7| R04Q2_5 0 |
Standardized
The item difficulty
The .61
standard.04|
error .98
for
|
6
1022
1293
-.7|
.96
-.9| .53
.51| 51.7 48.8| R04Q2_6 0 |
informationin logits
the estimate
|
7
686
1396
.19
.06| .98 -1.2| .97 -1.2| .41
.38| 66.7 65.8| R04Q2_7 0 |
weighted mean
|
8
2128
1419
-.93
.04|1.01
.2|1.09
1.5| .47
.48| 59.8 60.5| R04Q2_8 0 |
square statistic
…
|
30
1433
1177
-.60
.05|1.25
6.0|1.26
6.3| .19
.43| 58.2 64.4| R04Q7_1 0 |
|
31
750
1170
-.49
.07|1.02
.7| .98
-.4| .36
.37| 67.5 69.5| R04Q7_2 0 |
|
32
624
1092
-.11
.07|1.01
.4|1.00
.0| .37
.38| 66.4 66.8| R04Q7_3 0 |
|
33
635
1003
1.12
.05|1.20
4.7|1.27
5.1| .35
.48| 49.0 55.2| R04Q7_4 0 |
|
34
884
811
.85
.04|1.01
.3|1.01
.2| .58
.59| 40.8 40.9| R04Q7_5 0 |
|------------------------------------+----------+----------+-----------+-----------+------------|
| MEAN 1078.3 1255.1
.00
.05|1.00
-.2|1.01
-.1|
| 60.9 60.5|
|
| S.D.
498.2 167.6
.77
.01| .10
2.7| .15
2.8|
| 10.6
9.5|
|
-------------------------------------------------------------------------------------------------
An example of examinee responses (table 7.1
person: responses)
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NUMBER - NAME -- POSITION ------ MEASURE - INFIT (MNSQ) OUTFIT
Individual number
Test score
Individual
number
10
1,01
15
2,07
148
1,21
887 11121122211120112112121 1.68 1.4
RESPONSE:
1: 1 1 1 2 1 1 2 2 2 1
Z-RESIDUAL:
Fit statistics
1.2
Test score
RESPONSE:
Z-RESIDUAL:
11: 1 1 2 0 1
-3
1 2 1 1 2
RESPONSE:
Z-RESIDUAL:
21: 1 2 1 2 1
-3
2 2 2 1
1
Significantly
RESPONSE:
Z-RESIDUAL:
31: 1 2 1 1…………………………………………
negative
response
A number of responses with notes of significant deviations
(* — significantly negative,
+ — significantly positive)
Part А
| Part В
| Part С
11100 11100 11111 11011 11111 11110 10010 10001 10001 12213
**
*
*
*
+
11110 11011 11110 11011 11101 11111 01020 11111 11111 22213
*
*
*
*
*
*
*
*
+
11111 11111 11111 11111 11111 00000 10021 11002 11111 12000
*****
*
Item map (table 12)
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TABLE 12.2 Русский язык
ZOU000WS.TXT Mar 19 1:19 2012
INPUT: 1464 Person 34 Item REPORTED: 1464 Person 34 Item 90 CATS WINSTEPS 3.72.3
------------------------------------------------------------------------------------
4
3
2
1
Logits
0
-1
-2
-3
EACH
Person - MAP - Item
<more>|<rare>
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. T+
.## |
.# |
.## |T R04Q1_8
R04Q1_9
.### |
.#### |
.#### | R04Q7_4
.####### S+ R04Q1_3
.####### | R04Q7_5
.####### |S R04Q1_5
R04Q8_8
.####### | R04Q1_1
R04Q2_12
.########### | R04Q1_2
R04Q1_4
########## |
.########### M| R04Q2_1
R04Q2_7
.########## +M R04Q8_7
.########### | R04Q7_3
.######## | R04Q2_3
R04Q2_4
.######## | R04Q7_2
R04Q8_2
######## | R04Q7_1
R04Q8_3
.##### |S R04Q8_5
.##### S| R04Q2_10 R04Q2_8
.### + R04Q1_6
R04Q2_9
.### | R04Q2_11 R04Q2_2
.### |
.## |
.# |T
.## T|
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.# +
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+
<less>|<frequ>
"#" IS 9. EACH "." IS 1 TO 8
Mean (examinees)
R04Q2_6
R04Q1_7
R04Q2_5
R04Q8_6
R04Q8_1
R04Q8_4
Mean (items)
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Graphs
Item characteristic curve
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Confidence
interval
Empirical data
Model curve
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Category “0”
Category Probability Curve
Category “1”
Category “2”
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Item Information Function Curve
The lowest error of
measurement
The biggest
error of
measurement
The biggest
error of
measurement
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Test Information Function
The lowest error of
measurement
The biggest
error of
measurement
The biggest
error of
measurement
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Advantages and limitations of the
program
+
-
 Clear graphs and plots +
confidence intervals for
model and empirical item
characteristic curves (the
 Provides only Rasch
analysis, can not be used
for 2Pl or 3Pl analysis
boundary lines which indicate
upper and lower 95% two-sided
confidence intervals)
 A detailed and easy to
use manual
 Possibility of examinee
responses analysis
www.winsteps.com
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