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Mixed Model Selection via Profile Log-likelihood Juming Pan, Junfeng Shang Bowling Green State University, Ohio, USA Mixed models accommodating both fixed effects and random effects are widely utilized to describe the c
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Document Date: 2015-03-09 20:47:32
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File Size: 14,62 KB
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Facility
Junfeng Shang Bowling Green State University /
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Organization
Bowling Green State University /
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Position
model for generating the data /
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ProvinceOrState
Ohio /
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Technology
Newton-Raphson algorithm /
simulation /
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SocialTag
Estimation theory
Statistical models
Model selection
Random effects model
Bayesian information criterion
Likelihood function
Mixed model
Fixed effects model
Statistics
Regression analysis