Hierarchical Linear Regression – 2 Level Random Effects Model

Regression is a popular approach to modelling where a response variable is modelled as a function of certain predictors -┬áto understand the relations between variables. I used a linear model in a previous post, using the bread and peace model - and various ways to solve the equation. In this post, I want to fit … Continue reading Hierarchical Linear Regression – 2 Level Random Effects Model

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Compare Transformations & Batch Effects in Omics Data

While analysing high dimensional data, e.g. from Omics (Genomics, Transcriptomics, Proteomics etc.) - we are essentially measuring multiple response variables (i.e. genes, proteins, metabolites etc.) in multiple samples, resulting in a $latex rXn$ matrix X with r variables and n samples. The data capture can lead to multiple batches or groups in the data - … Continue reading Compare Transformations & Batch Effects in Omics Data