## Item Analysis, Test Design, and Classification |

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applied assume asymptotic distribution asymptotically normal basic elements bivariate Boolean algebra Boolean matrix algebra BSLP BSLP's characteristic vectors clusters compute consider consistent estimate correlation coefficients corresponding covariance matrix criterion defined denote density function determined dichotomous variables dimensional dispersion matrix distribution with mean eigen values eigen vectors elementary variables equation Euclidean space factor given Guttman scale independent instrumental variable joint distribution know the answer Lemma loss function maximize maximum mean squared error measure method multiple multivariate normal distribution normal with mean notation null hypothesis obtained order statistics orthogonal pairs population prediction principal component analysis probability probability vector problem procedure questions random variable regression respect root sample points score set of items simultaneous linear predictors subset subspace sum variables Test 5 Test tests based Theorem v-measure variation zero