Results 131 to 140 of about 97,995 (144)

On Testing Linear Hypothesis in a Nested Error Regression Model

Communications in Statistics - Theory and Methods, 2010
Consider the problem of testing the linear hypothesis on regression coefficients in the nested error regression model. The standard F-test statistic based on the ordinary least squares (OLS) estimator has the serious shortcoming that its type I error rates (sizes) are much larger than nominal significance levels, because the covariance matrix of data ...
Tatsuya Kubokawa, Nyambaa Erdembat
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Empirical Bayes methods in nested error regression models with skew-normal errors

Japanese Journal of Statistics and Data Science, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tsujino, Tatsuhiko, Kubokawa, Tatsuya
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Nesting, Crossing, Type IV Errors, and the Role of Statistical Models

American Educational Research Journal, 1978
Marascuilo and Levin’s use of the term “nesting” in previously published articles is idiosyncratic and contrary to well-established usage. Proper usage is described and illustrated. Their insistence on the usage of Scheffé tests on restricted sets of contrasts is opposed.
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Estimation of within Model Parameters in Regression Models with a Nested Error Structure

Journal of the American Statistical Association, 1992
Abstract Restricted randomizations, similar to those in split-plot type experiments, often are adapted to assign quantitative treatment factors to experimental units. Such restrictions result in the experiment having a nested error structure. Sufficient conditions are presented under which ordinary least squares (OLS) estimates of regressor parameters ...
Govinda J. Weerakkody, Dallas E. Johnson
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Comparison of the estimators of the intra-cluster correlation for the nested error regression model

Communications in Statistics - Simulation and Computation, 2015
ABSTRACTThe intra-cluster correlation is insisted on nested error regression model that, in practice, is rarely known. This article demonstrates the size in generalized least squares (GLS) F-test using Fuller–Battese transformation and modification F-test.
Sukanya Intarapak, Rawee Suwandechochai, Thidaporn Supapakorn   +2 more
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Corrected empirical Bayes confidence intervals in nested error regression models [PDF]

Journal of the Korean Statistical Society, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Prediction in a spatial nested error components panel data model

International Journal of Forecasting, 2014
Abstract This paper derives the Best Linear Unbiased Predictor (BLUP) for a spatial nested error components panel data model. This predictor is useful for panel data applications that exhibit spatial dependence and a nested (hierarchical) structure. The predictor allows for unbalancedness in the number of observations in the nested groups.
Badi H. Baltagi, Alain Pirotte
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A modified nested-error regression model for small area estimation

Statistics, 2013
A nested-error regression model having both fixed and random effects is introduced to estimate linear parameters of small areas. The model is applicable to data having a proportion of domains where the variable of interest cannot be described by a standard linear mixed model.
M. Herrador, M. D. Esteban, T. Hobza, D. Morales   +3 more
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EBLUPs Under Two-Fold Nested Error Regression Models

2020
This chapter derives empirical best predictors of additive parameters based on two-fold nested error regression models and pays special attention to the prediction of mean incomes, poverty proportions, and poverty gaps in small areas. The chapter calculates the distribution of the non-observed part of the population target vector conditioned to its ...
Domingo Morales, María Dolores Esteban, Agustín Pérez, Tomáš Hobza   +3 more
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Domain Mean Estimators Assisted by Nested Error Regression Models

2018
This paper introduces estimators of domain means assisted by nested error regression models. The new estimators are modifications of empirical best linear unbiased predictors that takes into account the sampling weights. They are obtained by summing up the model-based predicted values adjusted by a weighted sum residuals. The paper studies the sampling-
María Dolores Esteban, Domingo Morales, María del Mar Rueda   +2 more
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