Linear models for unbalanced data
著者
書誌事項
Linear models for unbalanced data
（Wiley series in probability and mathematical statistics, . Applied probability and statistics）
Wiley, c1987
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注記
Bibliography: p. 517-521
Includes index
内容説明・目次
内容説明
This presentation of the fundamentals of linear statistical models is devoted to unbalanced data (data having unequal numbers of observations in the subclasses) and its emphasis on the up-to-date cell means model approach to linear models for unbalanced data. Unbalanced data are harder to analyze and understand than balanced data, but are becoming more prevalent through computer storage of data. Topics covered include cell means models, 1-way classification, nested classifications, 2-way classification with some-cells-empty data, models with covariables, matrix algebra and quadratic forms, linear model theory, comments on computing packages, and much more. References and statistical tables are included.
目次
An Up--Dated Viewpoint: Cell Means Models. Basic Results for Cell Means Models: The 1--Way Classification. Nested Classifications. The 2--Way Classification with All--Cells--Filled Data: Cell Means Models. The 2--Way Classifications with Some--Cells Empty Data: Cells Means Models. Models with Covariables (Analysis of Covariance): The 1--Way Classification. Matrix Algebra and Quadratic Forms. Linear Model Theory: An Outline. The 2--Way Crossed Classification: Overparameterized Models. Cell Means Models: Some Generalizations. Models with Covariables: The General Case and Some Applications. Comments on Computing Packages. Mixed Models: A Thumbnail Survey. Index.
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