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Morris, John D.; Huberty, Carl J. – Multivariate Behavioral Research, 1987
The cross-validated classification accuracies of three predictor weighting strategies (least squares, ridge regression, and reduced rank) were compared under varying simulated data conditions for the two-group classification problem. Results were somewhat similar to previous findings with multiple regression when absolute rather than relative…
Descriptors: Algorithms, Multiple Regression Analysis, Predictor Variables, Simulation
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Clark, William H.; Margolis, Bruce L. – Educational and Psychological Measurement, 1971
Descriptors: Biographical Inventories, Data Analysis, Item Analysis, Scoring
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Rozeboom, William W. – Psychometrika, 1979
For idealized item configurations, equal item weights are often virtually as good for a particular predictive purpose as the item weights that are theoretically optimal. What has not been clear, however, is what happens to the similarity when the item configuration's variance structure is complex. (Author/CTM)
Descriptors: Multiple Regression Analysis, Predictor Variables, Scoring Formulas, Weighted Scores
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Keselman, H. J.; Keselman, Joanne C. – Journal of Educational Statistics, 1988
Two Tukey multiple comparisons and Bonferroni and multivariate approaches are compared for their rates of Type I error and any-pairs power when multisample sphericity was not satisfied and the design was unbalanced. For tests of weighted means and for study conditions investigated, the Bonferroni procedure provides a workable solution. (TJH)
Descriptors: Error of Measurement, Multivariate Analysis, Power (Statistics), Weighted Scores
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Commandeur, Jacques J. F.; Groenen, Patrick J. F.; Meulman, Jacqueline J. – Psychometrika, 1999
Presents two methods for including weights in distance-based nonlinear multivariate data analysis. One method assigns weights to the objects, while the other is concerned with differential weighing of groups of variables. Discusses applications of these weighting schemes and proposed an algorithm to minimize the corresponding loss function. (SLD)
Descriptors: Algorithms, Multidimensional Scaling, Multivariate Analysis, Research Methodology
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Qian, Jiahe – ETS Research Report Series, 2006
Weighting and variance estimation are two statistical issues involved in survey data analysis for large-scale assessment programs such as the Higher Education Information and Communication Technology (ICT) Literacy Assessment. Because survey data are always acquired by probability sampling, to draw unbiased or almost unbiased inferences for the…
Descriptors: Weighted Scores, Sampling, Statistical Analysis, Higher Education
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Wu, Chia-Huei; Yao, Grace – Social Indicators Research, 2006
Trauer and Mackinnon (2001; Quality of life research 10, pp. 579-585) recently proposed that weighting satisfaction scores by importance ratings in measuring quality of life is undesirable and unnecessary. However, they didn't use empirical data to support their claim. In this study, different weighting algorithms developed by Cummins (1997;…
Descriptors: Quality of Life, Life Satisfaction, Weighted Scores, Correlation
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Echternacht, Gary – Educational and Psychological Measurement, 1975
Estimates for the variances of empirically determined scoring weights are given. It is also shown that test item writers should write distractors that discriminate on the criterion variable when this type of scoring is used. (Author)
Descriptors: Scoring, Statistical Analysis, Test Construction, Test Reliability
Doppelt, Jermoe E. – Test Service Bulletin, 1957
The toal score concept is considered from the test user's point of views. The simples kind of total, obtained by adding raw scores on the tests, automatically assigns weights to the tests which are proportional to their standard deviation. When desired or appropriate, tests can be weighted equally in a total by transforming the raw scores on each…
Descriptors: Bulletins, Scoring, Statistical Analysis, Test Interpretation
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Hakstian, A. Ralph – Educational and Psychological Measurement, 1973
Descriptors: Mathematical Models, Measurement Techniques, Orthogonal Rotation, Tables (Data)
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Nemecek, Paul M. – Clearing House, 1994
Maintains that a weighted grading system may be more suitable in situations where traditional grading seems inadequate. Describes two categories of weighted systems: the multiplicative system and the additive system. (SR)
Descriptors: Elementary Secondary Education, Grades (Scholastic), Grading, Student Evaluation
English, Lyn D.; Watters, James J. – International Group for the Psychology of Mathematics Education, 2005
This paper reports on the mathematical modelling of four classes of 4th-grade children as they worked on a modelling problem involving the selection of an Australian swimming team for the 2004 Olympics. The problem was implemented during the second year of the children's participation in a 3-year longitudinal program of modelling experiences…
Descriptors: Mathematical Models, Grade 4, Longitudinal Studies, Qualitative Research
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Alon, Sigal; Tienda, Marta – American Sociological Review, 2007
This article uses four data sets to assess changes in the relative weights of test- and performance-based merit criteria on college enrollment during the 1980s and 1990s and considers their significance for affirmative action. Our results support the "shifting meritocracy" hypothesis, revealed by selective postsecondary institutions'…
Descriptors: Higher Education, Diversity (Institutional), Affirmative Action, Weighted Scores
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Raffeld, Paul – Journal of Educational Measurement, 1975
Results support the contention that a Guttman-weighted objective test can have psychometric properties that are superior to those of its unweighted counterpart, as long as omissions do not exist or are assigned a value equal to the mean of the k item alternative weights. (Author/BJG)
Descriptors: Multiple Choice Tests, Predictive Validity, Test Reliability, Test Validity
Razel, Micha; Eylon, Bat-Sheva – 1987
Conventional scoring of the Coloured Progressive Matrices (CPM) was compared with three methods of multiple weight scoring. The methods include: (1) theoretical weighting in which the weights were based on a theory of cognitive processing; (2) judged weighting in which the weights were given by a group of nine adult expert judges; and (3)…
Descriptors: Intelligence Tests, Measurement Techniques, Scoring, Test Validity
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