Results 261 to 270 of about 23,664,335 (320)
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2017
This chapter deals with the most relevant multi-dimensional random effects panel data models, where, unlike the case of fixed effects, the number of parameters to be estimated does not increase with the sample size. First, optimal (F)GLS estimators are presented for the textbook-style complete data case, paying special attention to asymptotics.
Balazsi, Laszlo +3 more
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This chapter deals with the most relevant multi-dimensional random effects panel data models, where, unlike the case of fixed effects, the number of parameters to be estimated does not increase with the sample size. First, optimal (F)GLS estimators are presented for the textbook-style complete data case, paying special attention to asymptotics.
Balazsi, Laszlo +3 more
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IEEE Transactions on Geoscience and Remote Sensing, 2019
High spatio-temporal resolution deformation series can be used to improve the understanding of deformation mechanism, thereby contributing to prevention and control of geological disasters such as mine subsidence, landslide, and earthquake.
Ning Liu +5 more
semanticscholar +1 more source
High spatio-temporal resolution deformation series can be used to improve the understanding of deformation mechanism, thereby contributing to prevention and control of geological disasters such as mine subsidence, landslide, and earthquake.
Ning Liu +5 more
semanticscholar +1 more source
Neurotoxicology and Teratology, 2019
"Intralitter likeness," the possibility that the shared genetic and/or maternal environment in multiparous species causes strong similarity for outcome variables in littermates, violates a core statistical assumption, that of observation independence ...
M. Golub, C. Sobin
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"Intralitter likeness," the possibility that the shared genetic and/or maternal environment in multiparous species causes strong similarity for outcome variables in littermates, violates a core statistical assumption, that of observation independence ...
M. Golub, C. Sobin
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A note regarding ‘random effects’
Statistics in Medicine, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Fixed Effects and Random Effects
2008One of the major benefits from using panel data as compared to cross-section data on individuals is that it enables us to control for individual heterogeneity. Not controlling for these unobserved individual specific effects leads to bias in the resulting estimates.
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2002
Abstract Chapter 8 has dealt with marginal models whose regression parameters have population average interpretations. In this chapter we consider random effects models in which the regression coeficients measure the more direct infiuence of explanatory variables on the responses for heterogeneous individuals.
Peter J Diggle +3 more
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Abstract Chapter 8 has dealt with marginal models whose regression parameters have population average interpretations. In this chapter we consider random effects models in which the regression coeficients measure the more direct infiuence of explanatory variables on the responses for heterogeneous individuals.
Peter J Diggle +3 more
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Effective Properties of Random Composites
SIAM Journal on Scientific Computing, 2004Summary: We propose a new concept of effective properties of composites with uncertain spatial arrangements of constitutive materials and within-material properties. Rather than replacing a heterogeneous property with a constant effective parameter, we seek to preserve the internal macrostructure of a composite.
TARTAKOVSKY D. M., GUADAGNINI, ALBERTO
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Quantum Mpemba Effect in Random Circuits.
Physical Review LettersThe essence of the Mpemba effect is that nonequilibrium systems may relax faster the further they are from their equilibrium configuration. In the quantum realm, this phenomenon arises in closed systems dynamics and is witnessed by features of symmetry ...
X. Turkeshi +2 more
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2009
Abstract In Chapter 5 we found overdispersion in the fabric fault data; the Poisson GLM did not fit or represent the data adequately. The failure of a generalized linear model to fit may be due to several causes. The distribution of Y may not be the specified exponential family member, or the regression model fitted may be mis-specified.
Murray Aitkin +3 more
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Abstract In Chapter 5 we found overdispersion in the fabric fault data; the Poisson GLM did not fit or represent the data adequately. The failure of a generalized linear model to fit may be due to several causes. The distribution of Y may not be the specified exponential family member, or the regression model fitted may be mis-specified.
Murray Aitkin +3 more
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Fixed- and Random-Effects Models
2021Deciding whether to use a fixed-effect model or a random-effects model is a primary decision an analyst must make when combining the results from multiple studies through meta-analysis. Both modeling approaches estimate a single effect size of interest.
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