IFILE= item output file

IFILE=filename produces an output file containing the information for each item. This file contains 4 heading lines (unless HLINES=N or ROW1HEADING=N), followed by one line for each item containing the following fields and the standard field selection. To change the output-field selection, go to the Output File menu, IFILE=, Field selection, Make default., or IOFSFIELDS=.

 

IFILE= file name

output file containing details. Usual file types: .txt, .xls

IFILE = ?

opens a Browser window to find the file

 

"Status=-2 to -6" means that there are no measurable responses by those items in this analysis. The items may be listed in the IFILE= and in Table 14, but all the numbers shown are default values. They have no meaning. Please do not include those items in summary statistics.

 

Columns:

with "Select All Fields" using Output File Field Selection

Start

End

Label

Format

Description

1

1

 

A1

Blank or ";" if HLINES=Y and there are no responses or deleted or extreme (status: 0,-1, -2, -3)

2

6

ENTRY

I5

1. The item sequence entry number

7

14

MEASURE

F8.2

2. Item's JMLE estimated difficulty calibration user-rescaled by UMEAN=, USCALE=, UDECIM=. Measures for deleted or inestimable items are shown as NOMEASURE=, which defaults to 9999.

15

17

STATUS

I3

3. The item's status:

2 = Anchored (fixed) measure

1 = Estimated measure

0 = Extreme maximum measure (estimated using EXTRSC=) for extreme maximum person raw score, or extreme minimum item raw score (-1 if USCALE= < 0)

-1 = Extreme minimum measure (estimated using EXTRSC=) for extreme minimum person raw score (usually 0), or extreme maximum item raw score (0 if USCALE= < 0)

-2 = No responses available for measure

-3 = Deleted by user. PDELETE=, PDFILE=, IDELETE=, IDFILE=, PSELECT=, ISELECT=

-4 = Inestimable: high (all responses in the same category with ISGROUPS=0 or CUTHI=)

-5 = Inestimable: low (all responses in the same category with ISGROUPS=0 or CUTLO=)

-6 = Anchored (fixed) measure with extreme (minimum or maximum) observed raw score

-7 to -16 = Temporarily deselected by Specification box with iSELECT= (usual STATUS - 10)

-17 to -26 = Temporarily deleted by Specification box with IDELETE= (usual STATUS - 20)

-27 to -36 = Temporarily deselected and deleted by Specification box with iSELECT= and iDELETE= (usual STATUS - 30)

18

25

COUNT

F8.1

4. The number of responses used in calibrating (TOTAL=N) or the observed count (TOTAL=Y)

26

34

SCORE

F9.1

5. The raw score used in calibrating (TOTAL=N) or the observed score (TOTAL=Y)

35

41

MODLSE

REALSE

F7.2

6. Standard error of the JMLE or WMLE item difficulty estimate adjusted by REALSE= and user-rescaled by USCALE=, UDECIM=

42

48

IN.MSQ

IN.CHI

F7.2

7. Item infit: mean square infit. Chi-square = IN.MSQ* INDF
If CHISQUARE=Yes, IN.CHI = Infit Chi-square

49

55

IN.ZSTD, ZEMP, LOG, PROB

F7.2

8. Item infit: t standardized, locally t standardized, log-scaled or probability of mean-square/chi-square (LOCAL=)

56

62

OUT.MS
OUT.CHI

F7.2

9. Item outfit: mean square outfit. Chi-square = OUT.MS * OUTDF
If CHISQUARE=Yes, OUT.CHI = Outfit Chi-square (= Yen's Q1 statistic)

63

69

OUT.ZSTD, ZEMP, LOG, PROB

F7.2

10. Item outfit: t standardized, locally t standardized, log-scaled or probability of mean-square/chi-square  (LOCAL=)

70

76

DISPLACE

F7.2

11. Item displacement (user-rescaled by USCALE=, UDECIM=)

77

83

PBSA, PTBIS=A

PBSX, PTBIS=Y

PTMA, PTBIS=N

PTMX, PTBIS=X

F7.2

12. Item by test-score correlation: point-biserial or point-measure. PTBIS=

PBSA = Point-Biserial correlation including all responses in the raw score

PBSX = Point-Biserial correlation excluding the current item's response from the raw score

PTMA = Point-Measure correlation including all responses for the measure

PTMX = Point-Biserial excluding the current item's response from the measure

84

90

WEIGHT

F7.2

13. Item weight IWEIGHT=

91

96

OBSMA

F6.1

14. Observed percent of observations within 0.5 score-points of their expected values

97

102

EXPMA

F6.1

15. Expected percent of observations within 0.5 score-points of their expected values

103

109

DISCRIM

F7.2

16. Item discrimination (this is not a parameter estimate, merely a descriptive statistic) DISCRIM=

110

115

LOWER

F6.2

17. Item lower asymptote: ASYMPTOTE=Yes

116

121

UPPER

F6.2

18. Item upper asymptote: ASYMPTOTE=Yes

122

127

PVALU

F6.2

19. Item proportion-correct-values or average ratings: PVALUE=Yes:

128

133

PBA-E

PBX-E, PBSX-E

PMA-E

PMX-E

F6.2

20. Expected value of Item by test-score correlation. PTBIS=

PBA-E = Expected value of Point-Biserial including all responses in the raw score

PBX-E = Expected value of Point-Biserial excluding the current response from the raw score

PMA-E = Expected value of Point-Measure including all responses in the measure

PMX-E = Expected value of Point-Biserial excluding the current response from the measure

134

139

RMSR

F6.2

21. Root-mean-square residual RMSR=

140

147

WMLE

F8.2

22. Warm's (Weighted) Mean Likelihood Estimate (WLE) of Item Difficulty user-rescaled by UMEAN=, USCALE=, UDECIM=

148

153

INDF

F6.2

23. degrees of freedom of Infit mean-square

154

159

OUTDF

F6.2

24. degrees of freedom of Outfit mean-square

160

167

QCMLE

F8.2

25. Quasi-CMLE estimates for dichotomous data. 0 otherwise.

 

 

 

 

If CMLE=Yes

 

 

CMLEM  

F8.2

CMLE item measure estimate

 

 

CMLESE

F8.2

CMLE item measure standard error

 

 

CMLEIms

F8.2

CMLE item INFIT mean-square fit statistic

 

 

CMLEIz

F8.2

CMLE item INFIT standardized fit statistic

 

 

CMLEOms

F8.2

CMLE item OUTFIT mean-square statistic

 

 

CMLEOz

F8.2

CMLE item OUTFIT standardized fit statistic

 

 

CMLEWML

F8.2

CMLE Warm Mean Likelihood item measure estimate

 

 

CMLEIdf

F8.2

CMLE item INFIT degrees of freedom

 

 

CMLEOdf

F8.2

CMLE item OUTFIT degrees of freedom

168

168

 

1X

 Blank

169

169

GROUPING

A1

26. Grouping to which item belongs (G) ISGROUPS=

170

170

 

1X

 Blank

171

171

MODEL

A1

27. Model used for analysis (R=Rating, S=Success, F=Failure) MODELS=

172

172

 

1X

 Blank

173

173

RECODE

A1

28. Recoding/Rescoring indicator:

"." = only CODES=

"A" = ALPHANUM=

"K" = KEY1=

"N" = RESCORE=2 and NEWSCORE=

"1" = RESCORE=1 and NEWSCORE=

Others = IREFER=

174

174

 

1X

 Blank

175

205

NAME

A30+

29. Item name or label: use ILFILE= for different item names

 

The format descriptors are:


In = Integer field width n columns


Fn.m = Numeric field, n columns wide including n-m-1 integral places, a decimal point and m decimal places


An = Alphabetic field, n columns wide


nX = n blank columns.

 

When CSV=Y, commas separate the values, which are squeezed together without spaces between. Quotation marks surround the "Item name", e.g., 1,2,3,4,"Name". When CSV=T, the commas are replaced by tab characters.

 

Example: You wish to write a text file on disk called "ITEMCAL.txt" containing the item statistics for use in updating your item bank, with values separated by commas:

  IFILE=ITEMCAL.txt

  CSV=Y

 

When W300=Yes, then this is produced in Winsteps 3.00, 1/1/2000, format:

 

Columns:

 

Start

End

Label

Format

Description

1

1

 

A1

Blank or ";" if HLINES=Y and there are no responses or deleted (status = -2, -3)

2

6

ENTRY

I5

1. The item sequence number

7

14

MEASURE

F8.2

2. Item's JMLE estimated calibration (user-rescaled by UMEAN=, USCALE=, UDECIM)

15

17

STATUS

I3

3. The item's status:

3 = Anchored (fixed) measure with extreme (minimum or maximum) observed raw score

2 = Anchored (fixed) measure

1 = Estimated measure

0 = Extreme minimum (estimated using EXTRSC=)

-1 = Extreme maximum (estimated using EXTRSC=)

-2 = No responses available for measure

-3 = Deleted by user

-4 = Inestimable: high (all responses in the same category with ISGROUPS=0 or CUTHI=)

-5 = Inestimable: low (all responses in the same category with ISGROUPS=0 or CUTLO=)

-6 = Deselected

18

23

COUNT

I6

4. The number of responses used in calibrating (TOTAL=N) or the observed count (TOTAL=Y)

24

30

SCORE

I6

5. The raw score used in calibrating (TOTAL=N) or the observed score (TOTAL=Y)

31

37

MODLSE

REALSE

F7.2

6. Item calibration's standard error with REALSE= and user-rescaled by USCALE=, UDECIM=

38

44

IN.MSQ

F7.2

7. Item mean square infit

45

51

ZSTD, ZEMP, LOG

F7.2

8. Item infit: t standardized (ZSTD), locally t standardized (ZEMP) or log-scaled (LOG)

52

58

OUT.MS

F7.2

9. Item mean square outfit

59

65

ZSTD, ZEMP, LOG

F7.2

10. Item outfit:t standardized (ZSTD), locally t standardized (ZEMP) or log-scaled (LOG)

66

72

DISPLACE

F7.2

11. Item displacement (user-rescaled by USCALE=, UDECIM=)

73

79

PBSA

PBSX

PTMA

PTMX

F7.2

12. Item by test-score correlation: point-biserial or point-measure. PTBIS=

PBSA = Point-Biserial correlation including all responses in the raw score

PBSX = Point-Biserial correlation excluding the current item's response from the raw score

PTMA = Point-Measure correlation including all responses for the measure

PTMX = Point-Biserial excluding the current item's response from the measure

80

80

 

1X

15. Blank

81

81

G

A1

16. Grouping to which item belongs, ISGROUPS=

82

82

 

1X

17. Blank

83

83

M

A1

18. Model used for analysis (R=Rating, S=Success, F=Failure) MODELS=

84

84

 

1X

19. Blank

85

132+

NAME

A30+

18. Item name

 

Example of IFILE= (to see other fields: : IFILE= Field Selection)

 

; ACT  LIKING FOR SCIENCE (Wright & Masters p.18)  Aug  8 22:17 2013

;ENTRY MEASURE ST   COUNT    SCORE MODLSE IN.MSQ IN.ZST OUT.MS OUT.ZS  DISPL   PBSA WEIGHT OBSMA EXPMA DISCRM LOWER UPPER PVALU PBA-E  RMSR    WMLE G M R NAME

     1    -.40  1    75.0    109.0    .21    .55  -3.48    .49  -2.53    .00    .69   1.00  77.0  61.7   1.52   .00  2.00  1.45   .53   .42    -.39 1 R . Watch birds

     2    -.71  1    75.0    116.0    .22    .93   -.39    .72  -1.02    .00    .66   1.00  74.3  64.4   1.26   .00  2.00  1.55   .50   .52    -.70 1 R . Read books on animals

 

Example: If you have your anchor values connected to unique item IDs (item labels), then

(1) put your item IDs and anchor values in an Excel table with the item IDs in the first column

(2) run an unanchored analysis in Winsteps. Output the IFILE= to Excel.

(3) VLOOKUP the item IDs in (2) using the Table in (1) to place the anchor values in the Measure column

(4) Save the entry number and measures from (2) to use as an anchor file.


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