Table 28.1 Person subtotal summaries on one line 
(controlled by PSUBTOT=, UDECIMALS=, REALSE=)
These summarize the measures from the main analysis for persons selected by PSUBTOT= (Table 28), including extreme scores. PSUBTOTAL= is useful for quantifying the impact of a test on different types of testtakers.
Table
28.2 Measure subtotals bar charts, controlled by PSUBTOT=
28.3 Measure subtotals summary statistics, controlled by PSUBTOT=
Subtotal specification is: PSUBTOTAL=@GENDER
Subtotals
EXTREME AND NONEXTREME KID SCORES

 KID MEAN S.E. MODEL MODEL 
 COUNT MEASURE MEAN P.SD S.SD MEDIAN SEPARATION RELIABILITY CODE 

 35 .37 .38 2.22 2.25 .26 1.87 .78 * 
 18 .68 .47 1.93 1.98 .26 1.61 .72 F 
 17 .05 .61 2.45 2.53 .26 2.04 .81 M 

SUBTOTAL RELIABILITY: .00
UMEAN=0 USCALE=1
Subtotal specification is: PSUBTOTAL=@GENDER 
identifies the columns in the Person label to be used for classifying the Person by @GENDER or whatever, using the column selection rules. 
EXTREME AND NONEXTREME SCORES 
All persons with estimated measures 
NONEXTREME SCORES ONLY 
Persons with nonextreme scores (omits Persons with 0% and 100% success rates) 
PERSON COUNT 
count of Persons. "PERSON" is the name assigned with PERSON= 
MEAN MEASURE 
average measure of Persons 
S.E. MEAN 
standard error of the average measure of Persons 
P.SD 
population standard deviation of the Persons. 
S.SD 
sample standard deviation of the Persons. 
MEDIAN 
the measure of the middle Person 
REAL/MODEL SEPARATION 
the separation coefficient: the "true" adjusted standard deviation / rootmeansquare measurement error of the Persons (REAL = inflated for misfit). 
REAL/MODEL RELIABILITY 
the Person measure reproducibility = ("True" Person measure variance / Observed variance) = Separation ² / (1 + Separation ²) 
CODE 
the classification code in the Person label. The first line, "*", is the total for all Persons. The remaining codes are those in the Person columns specified by @GENDER or whatever, using the column selection rules. In this example, "F" is the code for "Female" in the data file. "M" for "Male". It is seen that the two distributions are almost identical. 
SUBTOTAL RELIABILITY 
the reliability (reproducibility) of the means of the subtotals = true variance / observed variance = (observed variance  error variance) / observed variance. Observed variance = variance of MEAN MEASURES Error variance = meansquare of the S.E. MEAN 
Independentsamples ttest of pairs of subtotal means

 PERSON MEAN DIFFERENCE Welch 
 CODE CODE MEASURE S.E. t d.f. Prob. 

 F M .62 .77 .81 33 .424 

PERSON CODE 
the classification code in the Person label for subtotal "1" 
CODE 
the classification code in the Person label for subtotal "2" 
MEAN DIFFERENCE 
difference between the mean measures of the two CODE subtotals, "1" and "2" 
MEASURE 
size of the difference between "1" and "2" 
S.E. 
standard error of the difference = 
t 
Student's t = MEASURE / S.E. 
d.f. 
Welch's degrees of freedom 
Prob. 
twosided probability of Student's t. See tstatistics. 
Oneway ANOVA of subtotal means and variances
This reports a oneway analysis of variance for the subtotal means. Are they the same (statistically) as the overall mean?

 ANOVA  KID 
 Source SumofSquares d.f. MeanSquares Ftest Prob>F 

 @GENDER 3.41 1.00 3.41 .67 .5743 
 Error 169.12 33.00 5.12 
 Total 172.53 34.00 5.07 

 FixedEffects Chisquared: .6565 with 1 d.f., prob. .4178 

Source 
the variance component. 
@GENDER (the specified PSUBTOTAL= classification) 
the variation of the subtotal mean measures around the grand mean. 
Error 
Error is the part of the total variation of the measures around their grand mean not explained by the @GENDER 
Total 
total variation of the measures around their grand mean 
SumofSquares 
the variation around the relevant mean 
d.f. 
the degrees of freedom corresponding to the variation (= number of measures  1) 
MeanSquares 
SumofSquares divided by d.f. 
Ftest 
@GENDER MeanSquare / Error MeanSquare 
Prob>F 
the righttail probability of the Ftest value with (@GENDER, Error) d.f. A probability less than .05 indicates statistically significant differences between the means. 
FixedEffects ChiSquare (of Homogeneity) 
a test of the hypothesis that all the subtotal means are the same, except for sampling error 
d.f. 
degrees of freedom of chisquare = number of subtotals  1 
prob. 
probability of observing this value of the chisquare or larger if the hypothesis is true. A probability less than .05 indicates statistically significant differences between the means. 
inestimable 
some person counts are too small and/or some variances are zero. 
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