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Full-Text Articles in Medicine and Health Sciences
Propensity Score Modelling In Observational Studies Using Dimension Reduction Methods, Debashis Ghosh
Propensity Score Modelling In Observational Studies Using Dimension Reduction Methods, Debashis Ghosh
Debashis Ghosh
Conditional independence assumptions are very important in causal inference modelling as well as in dimension reduction methodologies. These are two very strikingly different statistical literatures, and we study links between the two in this article. The concept of covariate sufficiency plays an important role, and we provide theoretical justication when dimension reduction and partial least squares methods will allow for valid causal inference to be performed. The methods are illustrated with application to a medical study and to simulated data.
Joint Variable Selection And Classification With Immunohistochemical Data, Debashis Ghosh, Ratna Chakrabarti
Joint Variable Selection And Classification With Immunohistochemical Data, Debashis Ghosh, Ratna Chakrabarti
Debashis Ghosh
To determine if candidate cancer biomarkers have utility in a clinical setting, validation using immunohistochemical methods is typically done. Most analyses of such data have not incorporated the multivariate nature of the staining profiles. In this article, we consider modelling such data using recently developed ideas from the machine learning community. In particular, we consider the joint goals of feature selection and classification. We develop esti- mation procedures for the analysis of immunohistochemical profiles using the least absolute selection and shrinkage operator. These lead to novel and flexible models and algorithms for the analysis of compositional data. The techniques are …