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(controlled by ISUBTOT=, UDECIMALS=, REALSE=)
These summarize the measures from the main analysis for all items selected by ISUBTOT= (Table 27), including extreme scores. Bar charts are shown in Tables 27.2 . Detailed summary statistics in Table 27.3
Subtotal specification is: ISUBTOTAL=$S1W1
EXTREME AND NON-EXTREME SCORES
(NON-EXTREME SCORES ONLY)
----------------------------------------------------------------------
| ITEM MEAN S.E. OBSERVED MEDIAN REAL REAL ITEM |
| COUNT MEASURE MEAN S.D. SEPARATION RELIABILITY CODE |
|--------------------------------------------------------------------|
| 18 -.76 1.03 4.26 -1.96 3.73 .93 * |
| 10 -4.25 .57 1.70 -3.83 1.07 .53 0 |
| 2 4.80 .00 .00 4.80 .00 .00 1 |
| 2 5.47 .66 .66 5.47 .00 .00 2 |
| 1 2.24 - .00 2.24 .00 .00 3 |
| 3 2.04 .75 1.05 1.95 1.29 .62 4 |
----------------------------------------------------------------------
UMEAN=0 USCALE=1
Subtotal specification is: ISUBTOTAL=$S1W1
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identifies the columns in the item label to be used for classifying the item by $S1W1 or whatever, using the column selection rules.
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EXTREME AND NON-EXTREME SCORES
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All items with estimated measures
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NON-EXTREME SCORES ONLY
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Items with non-extreme scores (omits items with 0% and 100% success rates)
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ITEM COUNT
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count of items. "ITEM" is the name assigned with ITEM=
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MEAN MEASURE
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average measure of items
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S.E. MEAN
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standard error of the average measure of items
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OBSERVED S.D.
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population standard deviation of the items. Sample standard deviation is OBSERVED S.D. * sqrt ( COUNT / (COUNT-1))
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MEDIAN
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the measure of the middle item
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REAL/MODEL SEPARATION
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the separation coefficient: the "true" adjusted sample standard deviation / root-mean-square measurement error of the items (REAL = inflated for misfit).
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REAL/MODEL RELIABILITY
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the item measure reproducibility = ("True" item measure variance / Observed variance) = Separation² / (1 + Separation²)
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ITEM CODE
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the classification code in the item label. The first line, "*", is the total for all items. The remaining codes are those in the item columns specified by $S1W1 or whatever, using the column selection rules.
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------------------------------------------------
| ITEM MEAN DIFFERENCE Welch |
| CODE CODE MEASURE S.E. t d.f. Prob. |
|----------------------------------------------|
| 0 1 -9.06 .57 -15.95 10 .000 |
| 0 2 -9.72 .87 -11.14 10 .000 |
| 0 4 -6.29 .94 -6.71 11 .000 |
| 1 2 -.66 .66 -1.00 2 .423 |
| 1 4 2.77 .75 3.71 3 .034 |
| 2 4 3.43 1.00 3.44 3 .041 |
------------------------------------------------
ITEM CODE
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the classification code in the item label for subtotal "1"
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CODE
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the classification code in the item label for subtotal "2"
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MEAN DIFFERENCE
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difference between the mean measures of the two CODE subtotals, "1" and "2"
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MEASURE
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size of the difference between "1" and "2"
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S.E.
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standard error of the difference = sqrt ( (S.E. Mean "1")² + (S.E. Mean "2")² )
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t
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Student's t = MEASURE / S.E.
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d.f.
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Welch's degrees of freedom
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Prob.
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probability of Student's t. See t-statistics.
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