Introduction to Measurement Theory
This 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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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 intervals error of measurement error scores error variance exam examinee's examinees example factor analysis Figure formula scores frequency distribution generalizability theory 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 parallel tests percentile rank phi coefficient point-biserial correlation population prediction probability procedures produce Rasch's ratio raw scores raw-score regression line relationship sample scale values Section selection Spearman-Brown formula standard deviation standard error standardized scores statistical test developer test reliability test user test's total test scores trait value transformation true scores true-score variance validity coefficient variable