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Educational and Psychological… | 20 |

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Vegelius, Jan | 20 |

Edvardsson, Bo | 2 |

Janson, Svante | 1 |

Janson, Svante, | 1 |

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Journal Articles | 10 |

Reports - Research | 9 |

Guides - Non-Classroom | 1 |

Numerical/Quantitative Data | 1 |

Reports - Descriptive | 1 |

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Peer reviewed

Vegelius, Jan – Educational and Psychological Measurement, 1979

A new measure of similarity between persons applicable in Q-analysis is proposed. It allows assumptions of non-orthogonality between the items, across which the similarity is computed. The similarity measure may also be applied in an R-analysis. (Author/JKS)

Descriptors: Correlation, Item Analysis, Q Methodology, Test Construction

Peer reviewed

Vegelius, Jan; Edvardsson, Bo – Educational and Psychological Measurement, 1979

The G index and its generalizations in the six basic factor analytic designs are discussed. G should be used if there is no mutual direction of all the variables. G should also be used if the scale center is more suitable as a reference point than the mean value. (Author/CTM)

Descriptors: Correlation, Factor Analysis, Nonparametric Statistics, Q Methodology

Peer reviewed

Vegelius, Jan; And Others – Educational and Psychological Measurement, 1980

The Weighted H Index Delegate Discriminant Analysis method (WHIDD-analysis) is presented. It is rather similar to Holley's G-analysis, but does not utilize any component analysis and is thus cheaper and simpler to use. The WHIDD-analysis uses the weighted H-index as the E-correlation coefficient. (Author/BW)

Descriptors: Discriminant Analysis, Mathematical Formulas

Peer reviewed

Vegelius, Jan – Educational and Psychological Measurement, 1981

The G index is a measure of the similarity between individuals over dichotomous items. Some tests for the G-index are described. For each case an example is included. (Author/GK)

Descriptors: Hypothesis Testing, Mathematical Formulas, Mathematical Models, Nonparametric Statistics

Peer reviewed

Vegelius, Jan – Educational and Psychological Measurement, 1979

The computer program WEIGAN makes the weighted G analysis available for computer users. The input and output of the program are described. (Author/JKS)

Descriptors: Computer Programs, Correlation, Factor Analysis, Item Analysis

Peer reviewed

Vegelius, Jan – Educational and Psychological Measurement, 1982

The possibility of using a Q-analysis also for nominal data is discussed, using the J-index as a measure of similarity between persons. An example is given when ten persons sorted 16 playing cards into as many groups as they wished. A Q-analysis of these data gave a natural two-dimensional structure. (Author/BW)

Descriptors: Correlation, Factor Analysis, Mathematical Models, Statistical Analysis

Peer reviewed

Janson, Svante; Vegelius, Jan – Educational and Psychological Measurement, 1980

A general discriminant analysis method, based on the E-correlation coefficient concept is introduced, and separates the various subgroups by using Euclidean spaces. The G-analysis, the weighted G analysis and the WHIDD analysis are special cases of the method. (Author/RL)

Descriptors: Comparative Analysis, Discriminant Analysis

Peer reviewed

Vegelius, Jan – Educational and Psychological Measurement, 1980

One argument against the G index is that, unlike phi, it is not a correlation coefficient; yet, G conforms to the Kendall and E-coefficient definitions. The G index is also equal to the Pearson product moment correlation coefficient obtained from double scoring. (Author/CP)

Descriptors: Correlation, Mathematical Formulas, Test Reliability

Peer reviewed

Vegelius, Jan – Educational and Psychological Measurement, 1979

The G index is a measure of similarity between pairs of dichotomized items. The G index is generalized here to the case where items are trichotomized. (JKS)

Descriptors: Correlation, Item Analysis, Nonparametric Statistics, Technical Reports

Peer reviewed

Janson, Svante,; Vegelius, Jan – Educational and Psychological Measurement, 1980

The value of the phi coefficient cannot, in general, be uniquely determined from the G index. G is more suitable than the phi coefficient as a measure of similarity between individuals, because phi is too unstable over item reflection. (Author/RL)

Descriptors: Comparative Analysis, Mathematical Formulas, Measurement Techniques

Peer reviewed

Vegelius, Jan – Educational and Psychological Measurement, 1978

G analysis is a type of discriminant analysis. A generalization of the G analysis to cases where variables are on an interval or ordinal scale is described. The placement system used in the description is distance-based, but other systems may also be applied. (Author/JKS)

Descriptors: Discriminant Analysis, Measurement Techniques, Statistical Analysis

Peer reviewed

Vegelius, Jan – Educational and Psychological Measurement, 1977

Generalizations of the G index as a measure of similarity between persons beyond the dichotomous situation are discussed. An attempt is made to present a generalization that does not require dichotomization of the items for cases where the number of response alternatives may differ. (Author/JKS)

Descriptors: Correlation, Item Analysis, Measurement Techniques, Multidimensional Scaling

Peer reviewed

Vegelius, Jan – Educational and Psychological Measurement, 1977

The G index of agreement does not permit the use of various weights for its various items. The weighted G index described here, make it possible to use unequal weights. An example of the procedure is provided. (Author/JKS)

Descriptors: Correlation, Item Analysis, Multidimensional Scaling, Test Items

Peer reviewed

Vegelius, Jan – Educational and Psychological Measurement, 1978

The E (for Euclidean) correlation coefficient is introduced as a general formulation of a variety of measures of association. Characteristics of the coefficient are discussed, and 23 measures of association are shown to be or not be E coefficients. (JKS)

Descriptors: Correlation, Nonparametric Statistics, Predictor Variables, Research Design

Peer reviewed

Vegelius, Jan – Educational and Psychological Measurement, 1978

A computer program for computing coefficients for nominal scales, such as the contingency coefficient, Cramer's V, and others is described. (Author/JKS)

Descriptors: Computer Programs, Correlation, Nonparametric Statistics, Tables (Data)

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