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Mann-Whitney Test with Adjustments to Pre-treatment Variables for Missing Values and Observational Study
Dimension reduction Kernel smoothing Mann-Whitney statistic
2016/1/20
The conventional Wilcoxon/Mann-Whitney test can be invalid for comparing treatment effects in the presence of missing values or in observational studies. This is because the missingness of the outcome...
Missing values and sparse inverse covariance estimation
Missing values sparse inverse covariance estimation
2010/3/19
We propose an `1-regularized likelihood method for estimating the inverse
covariance matrix in the high-dimensional multivariate normal model
in presence of missing data. Our method is based on the ...
Empirical likelihood for estimating equations with missing values
Empirical likelihood estimating equations Kernel estimation missing values nonparametric imputation
2010/3/18
We consider an empirical likelihood inference for parameters defined
by general estimating equations when some components of the
random observations are subject to missingness. As the nature of the
...
Missing values：processing with the Kohonen algorithm
Missing values processing Kohonen algorithm
2010/4/26
Missing values：processing with the Kohonen algorithm。