Table 11 Responses used to calculate bias estimates |
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Table 11 summarizes the response modeling in the bias analysis
Bias/Interaction: 1. Student, 2. Format
+--------------------------------------------------+
| Cat Score Exp. Resd StRes| |
|-----------------------------+--------------------|
| 9.60 9.60 9.60 .01 .01 | Mean (Cnt: 296) |
| 1.34 1.34 1.30 .31 .53 | S.D. (Population) |
| 1.34 1.34 1.30 .31 .53 | S.D. (Sample) |
+--------------------------------------------------+
Count of measurable responses = 296.00
Raw-score variance of observations = 1.80 100.00%
Variance explained by Rasch measures = 1.53 85.00%
Variance of residuals = 0.27 15.00%
Variance explained by bias/interactions = 0.18 10.00%
Variance remaining in residuals = 0.09 5.00%
Identification |
Meaning |
Cat |
Observed value of the category in the data file |
Score |
Value of category in this analysis. This is less than Cat. if there are structural zeroes. |
Exp. |
Expected score based on current measures |
Resd |
Residual, the score difference between Score and Exp. |
StRes |
The residual divided by its standard error. The Rasch model is now over-parameterized, so the standardized residuals are expected to have an S.D. less than 1.0. |
Mean |
average of the observations |
Cnt: |
Count is the number of observations |
S.D. (Population) |
standard deviation treating this sample as the entire population |
S.D. (Sample) |
standard deviation treating this sample as a sample from the population. It is larger than S.D. (Population). |
Count of measurable responses |
the number of ratings used in estimating the bias terms. This may be only a small fraction of the entire data set. |
Raw-score variance of observations |
square of S.D. (Population) of Score in Table 11 |
Variance explained by Rasch measures |
from Table 5 |
Variance of residuals |
from Table 5 |
Variance explained by bias/interactions |
Variance of Residuals - Variance remaining in residuals |
Variance remaining in residuals |
square of S.D. (Population) of Resd in Table 11 |
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