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Dimension reduction and alleviation of confounding for spatial generalized linear mixed models
John Hughes, Murali Haran
Biostatistics
Research output
:
Contribution to journal
›
Article
›
peer-review
226
Scopus citations
Overview
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Dive into the research topics of 'Dimension reduction and alleviation of confounding for spatial generalized linear mixed models'. Together they form a unique fingerprint.
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Mathematics
Generalized Linear Mixed Model
64%
Confounding
63%
Dimension Reduction
58%
Spatial Data
19%
Random Effects
15%
Infant Mortality
12%
Disease Mapping
11%
Data Modeling
9%
Inflation
8%
Binary Data
8%
Ecology
8%
Count Data
8%
Bayesian inference
7%
Regression Coefficient
7%
Parameterization
7%
Count
6%
High-dimensional
6%
Regression
5%
Binary
5%
Model
4%
Business & Economics
Dimension Reduction
100%
Generalized Linear Mixed Model
79%
Confounding
58%
Random Effects
13%
Spatial Regression
9%
Bayesian Inference
9%
Data Modeling
8%
Count Data
8%
Infant Mortality
8%
Regression Coefficient
7%
Ecology
5%
Inference
5%