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Factor Analysis | 7 |

Correlation | 5 |

Matrices | 5 |

Computer Programs | 4 |

Multivariate Analysis | 3 |

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Item Sampling | 2 |

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Educational and Psychological… | 13 |

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Kaiser, Henry F. | 13 |

Cerny, Barbara A. | 4 |

Michael, William B. | 2 |

Serlin, Ronald C. | 2 |

Dickman, Kern W. | 1 |

Hunka, Steve | 1 |

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Journal Articles | 5 |

Reports - Research | 4 |

Reports - Descriptive | 1 |

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Peer reviewed

Kaiser, Henry F. – Educational and Psychological Measurement, 1974

Descriptors: Computer Programs, Factor Analysis, Matrices, Multivariate Analysis

Peer reviewed

Kaiser, Henry F.; Michael, William B. – Educational and Psychological Measurement, 1975

An alternative derivation of Tryon's basic formula for the coefficient of domain validity or the coefficient of generalizability developed by Cronbach, Rajaratnam, and Glaser is provided. This derivation, which is also the generalized Kuder-Richardson coefficient, requires a relatively minimal number of assumptions compared with that in previously…

Descriptors: Matrices, Sampling, Statistical Analysis, Test Reliability

Peer reviewed

Serlin, Ronald C.; Kaiser, Henry F. – Educational and Psychological Measurement, 1976

Internal consistency as one rationale for item selection from the unverse of possible test items is discussed and formulae are presented which relate the maximum internal consistency of a test to the largest eigenvalue of the interitem correlation matrix. A computer program to perform these calculations is presented. (Author/JKS)

Descriptors: Computer Programs, Item Sampling, Matrices, Test Construction

Peer reviewed

Kaiser, Henry F. – Educational and Psychological Measurement, 1981

A revised version of Kaiser's Measure of Sampling Adequacy for factor-analytic data matrices is presented. (Author)

Descriptors: Correlation, Factor Analysis, Research Problems, Sampling

Peer reviewed

Kaiser, Henry F.; Cerny, Barbara A. – Educational and Psychological Measurement, 1979

Whether to factor the image correlation matrix or to use a new model with an alpha factor analysis of it is mentioned, with particular reference to the determinacy problem. It is pointed out that the distribution of the images is sensibly multivariate normal, making for "better" factor analyses. (Author/CTM)

Descriptors: Correlation, Factor Analysis, Matrices, Oblique Rotation

Peer reviewed

Kaiser, Henry F. – Educational and Psychological Measurement, 1980

The use of Bayes' estimates for proportions in the Law of Comparative Judgment is suggested to avoid sample proportions of zero and one. (Author)

Descriptors: Bayesian Statistics, Comparative Analysis, Reliability, Statistical Analysis

Peer reviewed

Kaiser, Henry F.; Cerny, Barbara A. – Educational and Psychological Measurement, 1980

A simplified mathematical and computational treatment of the canonical correlational analysis of two-way contingency tables is provided. (Author)

Descriptors: Multivariate Analysis

Peer reviewed

Kaiser, Henry F.; Cerny, Barbara A. – Educational and Psychological Measurement, 1979

A method for obtaining teacher ratings from incomplete student ranking data is presented. The procedure involves finding the scores for the teachers on the first principal component of a student intercorrelation matrix, where the missing data are supplied by least squares. (Author)

Descriptors: Correlation, Data Analysis, Factor Analysis, Matrices

Peer reviewed

Kaiser, Henry F.; Michael, William B. – Educational and Psychological Measurement, 1977

A formula is derived for ascertaining factor scores for the factor analytic method: Little Jiffy, Mark IV. This formula is then employed to derive a second formula giving an exact determination of the generalized Kuder-Richardson estimate of the reliability of scores on a Little Jiffy factor. (Author/JKS)

Descriptors: Factor Analysis, Reliability, Scores, Scoring Formulas

Peer reviewed

Cerny, Barbara A.; Kaiser, Henry F. – Educational and Psychological Measurement, 1978

This note described a FORTRAN IV, CDC, computer program for the canonical analysis of a two-way contingency table. (Author)

Descriptors: Computer Programs, Correlation, Multivariate Analysis, Nonparametric Statistics

Peer reviewed

Serlin, Ronald C.; Kaiser, Henry F. – Educational and Psychological Measurement, 1978

When multiple-choice tests are scored in the usual manner, giving each correct answer one point, information concerning response patterns is lost. A method for utilizing this information is suggested. An example is presented and compared with two conventional methods of scoring. (Author/JKS)

Descriptors: Correlation, Factor Analysis, Item Analysis, Multiple Choice Tests

Peer reviewed

Kaiser, Henry F.; Hunka, Steve – Educational and Psychological Measurement, 1973

Authors conclude that, in the world of real data sample correlation matrices, Guttman's stronger lower bound is not of practical use in determining the effective number of common factors. (Authors/CB)

Descriptors: Factor Analysis, Factor Structure, Item Sampling, Mathematical Applications

Peer reviewed

Kaiser, Henry F.; Dickman, Kern W. – Educational and Psychological Measurement, 1972

Descriptors: Computer Programs, Data Analysis