Showing papers on "Mixed model published in 1974"

A predictive approach to the random effect model

Abstract: SUMMARY Two simple estimators are derived here for the means of the random effect model by means of predictive sample reuse. They are applied to two sets of data in the literature and compared with several other procedures. The mixed model is also discussed.

The Invariance and Calculation of Method 2 for Estimating Variance Components

Abstract: Three methods of estimating variance components from unbalanced data are given in Henderson [1953]. Method 2, designed to circumvent biasedness that results from using MIethod 1 on mixed models, is characterized more generally in Searle [1968] as a special way of executing what is described there as a simplified form of a Generalized Method 2. In that description 2 limitations are discussed: (i) It is proven that the simplified form of the Generalized M\l[ethod 2 can be used only when there are no interactions between fixed and random factors. (ii) It is suggested that the Generalized Method 2 is not uniquely specified. There is no doubt about limitation (i): Henderson's Method 2 can be used only when the model has no interactions between fixed and random effects. However, we show here for a wide class of -models that Henderson's Method 2, despite being one of the methods collectively called Generalized Method 2, does not suffer from limitation (ii). Indeed, it is a generalization of limitation (i) that nullifies (ii); i.e., for a wide class of models, Method 2 is well defined. One comment on limitation (i) is appropriate. Models that include any nesting of fixed and random factors within each other are also excluded from Method 2, because such models are tantamount to having interactions between fixed aind random factors.

Some Differences Between Fixed, Mixed, and Random Effects Analysis of Variance Models

Abstract: The analysis of variance is a technique for comparing treatment means or for estimating components of variation. The former is called fixed effects analysis of variance and the latter is called random effects analysis of variance. Many nonstatisticians ..

More on Extended Complete Block Designs

Abstract: Augmenting complete blocks of t units with k additional units (1 < k < t) to form blocks of size t + k enables the separate estimation of nonadditivity and experimental error. The removal of the measure of nonadditivity (however small) from the residual variation in a fixed effects model results in a more efficient test when comparing treatment effects. Variance component estimation in a two-way mixed model with interaction is also mentioned.

Metodyka i cele badania zmienności parametrów złożowych

Abstract: THE METHOD AND AIMS OF STUDIES ON VARIABILITY OF DEPOSITS PARAMETERS Summary Description of variability of deposit parameters is made on the basis of a deterministic, probabilistic or mixed model. Deterministic model assumes a relationship between parameters value and position of observation points. Probabilistic model accepts random parameters deviations. Mixed model assumes that on the basis of casual deviations it is possible to observe systematic, non-random changes of values of parameters. They may be oriented or periodic. Separation of non-random variability component from the background of random deviations is made by means of mean-moving trend, correlation and spectral analyses. Basic principles of the methodology of determination of reconaissance network in relation to variation of deposits parameters and possibilities of utilization of various studies for solving problems of genesis of deposits are discussed. The discussion is illustrated by the results• of studies on sulphur deposits.