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Robust Score Tests With Missing Data in Genomics Studies
Kin Yau Wong
, Donglin Zeng
, D. Y. Lin
Department of Applied Mathematics
The Hong Kong Polytechnic University
Research output
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Journal article publication
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Journal article
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Academic research
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peer-review
5
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Citations (Scopus)
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Dive into the research topics of 'Robust Score Tests With Missing Data in Genomics Studies'. Together they form a unique fingerprint.
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Keyphrases
Missing Data
100%
Score Test
100%
Genomic Studies
100%
Imputation Model
100%
Score Statistic
75%
Misspecified
50%
Statistical Methods
25%
Simulation Study
25%
Invalid
25%
Approximation Theory
25%
Linear Predictor
25%
Semi-parametric
25%
Asymptotic Distribution
25%
Genomic Data
25%
Empirical Process Theory
25%
Cancer Genomics
25%
Variance Estimator
25%
Asymptotically Unbiased
25%
Semiparametric Regression Model
25%
Arbitrary Functions
25%
Single Imputation
25%
Imputed Values
25%
Posterior Expectation
25%
Imputed Data
25%
Spline-based Methods
25%
Missing Data Mechanism
25%
Phenotype Model
25%
Sieve Approximation
25%
Mathematics
Missing Value
100%
Score Statistic
100%
Score Test
100%
Empirical Process
33%
Variance Estimator
33%
Imputed Value
33%
Semiparametric Regression Model
33%
Missing Data Mechanism
33%
Simulation Study
33%
Spline
33%
Linear Predictor
33%
Single Imputation
33%
Approximation Theory
33%
Asymptotic Distribution
33%
Supplementary Material
33%
Arbitrary Function
33%