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title: "Using MetaHD: A multivariate meta-analysis model for metabolomics data" | ||
author: "Jayamini C. Liyanage, Luke Prendergast, Robert Staudte and Alysha De Livera" | ||
date: "2024-06-22T21:26:11Z" | ||
tags: [Multivariate, Meta-Analysis, Metabolomics, Package] | ||
link: "https://bookdown.org/a2delivera/MetaHD/" | ||
length_weight: "3.3%" | ||
repo: "rstudio/bookdown-demo" | ||
pinned: false | ||
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MetaHD is an R package that performs multivariate meta-analysis for high-dimensional metabolomics data for integrating and collectively analysing individual-level metabolomics data generated from multiple studies as well as for combining summary estimates. This approach accounts for correlation between metabolites, considers variability within and between studies, handles missing values and uses shrinkage estimation to allow for high dimensionality. |
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4 changes: 2 additions & 2 deletions
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content/archive/internal/paulcbauer-applied-data-visualization.md
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title: "An R Companion to Applied Regression" | ||
author: "Peter Baumgartner" | ||
date: "2024-06-15T21:00:07Z" | ||
date: "2024-06-23T09:11:57Z" | ||
tags: [Textbook] | ||
link: "https://bookdown.org/pbaumgartner/car-fox-weisberg/" | ||
length_weight: "9.9%" | ||
length_weight: "10.6%" | ||
pinned: false | ||
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Peter Baumgartner I have finished until chapter 3.3 and additionally, 3.5, 4.1 and 4.2. I am currently working on 3.4 (Transforming Data). WATCH OUT: This is my personal learning material and is therefore neither an accurate replication nor an authoritative textbook. I am writing this book as a text for others to read because that forces me to become explicit and explain all my learning outcomes more carefully. Please keep in mind that this text is not written by an expert but by a learner. Text passages with content I am already familiar I have skipped. Section of the original text where I ... | ||
Peter Baumgartner I have finished until chapter 3. Currently I am working on section 4.2 “Multiple linear regression”. WATCH OUT: This is my personal learning material and is therefore neither an accurate replication nor an authoritative textbook. I am writing this book as a text for others to read because that forces me to become explicit and explain all my learning outcomes more carefully. Please keep in mind that this text is not written by an expert but by a learner. Text passages with content I am already familiar I have skipped. Section of the original text where I needed more in-depth ... |
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content/archive/internal/pbaumgartner-inequality-austria.md
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title: "Inequality in Austria" | ||
author: "Peter Baumgartner" | ||
date: "2024-06-26T10:27:41Z" | ||
tags: [Textbook] | ||
link: "https://bookdown.org/pbaumgartner/inequality-austria/" | ||
length_weight: "2%" | ||
pinned: false | ||
--- | ||
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Peter Baumgartner WATCH OUT: This is work in progress This is my personal learning material and is therefore neither a scientific peer reviewed article nor an authoritative textbook. With this book I want to apply my statistical knowledge using the R language to investigate social inequality for Austria, my country of birth and where I am living. As an advanced organizer I will take “A Brief History of Euqality” by Thomas Piketty (Piketty 2022). I am writing this book as a text for others to read because that forces me to become explicit and explain all my learning outcomes more carefully. ... |
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title: "Introduction to Regression Methods for Public Health Using R" | ||
author: "Ramzi W. Nahhas" | ||
date: "2024-06-17T13:57:09Z" | ||
tags: [Statistics, Course] | ||
date: "2024-06-21T21:19:30Z" | ||
tags: [Statistics] | ||
link: "https://bookdown.org/rwnahhas/RMPH/" | ||
length_weight: "100%" | ||
pinned: false | ||
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An introduction to regression methods using R with examples from public health datasets and accessible to students without a background in mathematical statistics. [...] This is a DRAFT but is still undergoing final revisions. The goal is publication as a printed version (through CRC Press) with the online version remaining freely available. Status If you have any comments or suggestions, feel free to contact me at [email protected]. Thank you! This text is suitable as a second biostatistics course for Master of Public Health students or public health professionals. Almost all public ... | ||
An introduction to regression methods using R with examples from public health datasets and accessible to students without a background in mathematical statistics. [...] This text will soon be in press, published by CRC ... |
4 changes: 2 additions & 2 deletions
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content/archive/internal/salmonwatersheds-tech-report-staging.md
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title: "STAT 136: Introduction to Regression Analysis" | ||
author: "Siegfred Roi L. Codia" | ||
date: "2024-06-20T03:12:15Z" | ||
date: "2024-06-26T16:02:52Z" | ||
tags: [Course] | ||
link: "https://bookdown.org/slcodia/Stat_136/" | ||
length_weight: "9.4%" | ||
length_weight: "1.9%" | ||
pinned: false | ||
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This is a book developed by Siegfred Codia for Stat 136 class in UP Diliman. [...] Linear regression model; model selection; regression diagnostics; use of dummy variables; remedial measures. Prereq: Stat 131, Stat 135. 3h. 3 u. The course is mainly divided into 3 parts: (1) Preliminaries and Introduction, (2) Model Building, and (3) Diagnostic Checking. The following is the complete outline: 2 Problem Sets (30%) You will be tasked to solve a set of problems. The exercises might be a theoretical problem that you need to solve analytically, or a machine problem, wherein you need to answer ... | ||
This is a book developed by Siegfred Codia for Stat 136 class in UP Diliman. [...] Linear regression model; model selection; regression diagnostics; use of dummy variables; remedial measures. Prereq: Stat 131, Stat 135. 3h. 3 u. The course shall equip the learners with the foundation necessary to perform linear regression analysis. The learners are also expected to apply the learnings in this course to higher Stat courses. The course is mainly divided into 3 parts: (1) Preliminaries and Introduction, (2) Model Building, and (3) Diagnostic Checking. The following is the complete outline: ... |
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