Introduction to Measurement TheoryThis book is intended to serve as a text and reference book for people who are using or constructing psychological tests and interpreting test scores and scales. It is designed for people who understand collage algebra and who have some famuliarity with elementary statistics, for those lacking this familiarity or desiring a review. |
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Page 161
... scores to an array of criteria . Local norms , rather than norms based on a national sample , may be necessary for specific school programs ... standardized score . 7.5 Standard and Standardized Scores 161 Standard and Standardized Scores.
... scores to an array of criteria . Local norms , rather than norms based on a national sample , may be necessary for specific school programs ... standardized score . 7.5 Standard and Standardized Scores 161 Standard and Standardized Scores.
Page 162
Mary J. Allen, Wendy M. Yen. the standard score and Y is the standardized score . For example , if you want to have μ * = 100 and σ * = 16 , the transformation from Z to Y would be : Y = 16Z + 100. An examinee with a standard score of 2 ...
Mary J. Allen, Wendy M. Yen. the standard score and Y is the standardized score . For example , if you want to have μ * = 100 and σ * = 16 , the transformation from Z to Y would be : Y = 16Z + 100. An examinee with a standard score of 2 ...
Page 164
... standard scores to standardized scores with a desired mean and standard deviation . To illustrate this process , we will normalize the raw scores given in Table 7.8 to have a transformed - score mean of 100 and standard deviation of 10 ...
... standard scores to standardized scores with a desired mean and standard deviation . To illustrate this process , we will normalize the raw scores given in Table 7.8 to have a transformed - score mean of 100 and standard deviation of 10 ...
Contents
Introduction | 1 |
Classical TrueScore Theory | 56 |
Reliability | 72 |
Copyright | |
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assumptions base rate binomial-error model biserial calculate ceiling effect Chapter classical true-score theory confidence intervals correlation coefficient criterion scores criterion-referenced tests cutting score dichotomous discrimination equal error of measurement error scores error variance exam examinee's examinees example expected factor analysis Figure formula scores frequency distribution grade scores homoscedasticity information function interpretation item difficulty item-characteristic curve large number latent latent-trait models latent-trait values level of measurement linear logistic model mean measurement theory method normal distribution normal-ogive number of items observed scores observed test scores observed-score variance obtained p₁ parallel tests phi coefficient point-biserial correlation population prediction probability procedures produce Rasch's ratio raw scores regression line relationship sample scale values Section selection Spearman-Brown formula standard deviation standard error standardized scores statistical Table test developer test reliability test user test's total test scores trait value transformation true scores true-score variance validity coefficient variable X₁ Y₁ στ