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Nonparametric Regression with Discrete Covariate and Missing Values
Nonparametric Regression Discrete kernel smoothing Imputation Missing Values Variance Reduction
2016/1/19
We consider nonparametric regression with a mixture of continuous and discrete ex-planatory variables where realizations of the response variable may be missing. An impu-tation based nonparametric reg...
Regularity Properties of High-dimensional Covariate Matrices
high-dimensional regression instrumental variables sparse estimation compressed sensing random matrix re-stricted eigenvalue compatibility,ℓ q sensitivity computational complex-ity NP-hardness
2013/6/14
Regularity properties such as the incoherence condition, the restricted isometry property, compatibility, restricted eigenvalue and $\ell_q$ sensitivity of covariate matrices play a pivotal role in hi...
Sequential estimation for covariate-adjusted response-adaptive designs
Covariate-adjustment logistic regression response-adaptive design se-quential estimation
2011/7/6
In clinical trials, a covariate-adjusted response-adaptive (CARA) design allows a subject newly entering a trial a better chance of being allocated to a superior treatment regimen based on cumulative ...
Covariate adjusted functional principal components analysis for longitudinal data
Functional data analysis functional principal componentsanalysis local linear regression longitudinal data analysis smoothing sparse data
2010/3/11
Classical multivariate principal component analysis has been extended
to functional data and termed functional principal component
analysis (FPCA). Most existing FPCA approaches do not accommodate
...
Statistical Analysis for Longitudinal Counting Data in the Presence of a Covariate Considering Different
Statistical Analysis Longitudinal Counting Data
2009/9/17
Statistical Analysis for Longitudinal Counting Data in the Presence of a Covariate Considering Different "Frailty" Models。
A Comparison of Analysis of Covariate-Adjusted Residuals and Analysis of Covariance
allometry ANOVA clustering homogeneity of variances isometry Kruskal-Wallis test linearmodels parallel lines model
2010/3/19
Various methods to control the influence of a covariate on a response variable are compared. In particular,ANOVA with or without homogeneity of variances (HOV) of errors and Kruskal-Wallis (K-W) tests...
Testing polynomial covariate effects in linear and generalized linear mixed models
Likelihood Ratio Test Restricted Maximum Likelihood （REML） Score Test
2009/2/11
An important feature of linear mixed models and generalized linear mixed models is that the conditional mean of the response given the random effects, after transformed by a link function, is linearly...
Covariate Balance in Simple，Stratified and Clustered Comparative Studies
Cluster contiguity community intervention group randomization randomization inference subclassification
2010/4/30
In randomized experiments, treatment and control groups
should be roughly the same—balanced—in their distributions of pretreatment
variables. But how nearly so? Can descriptive comparisons
meaningf...