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Provides datasets for Introduction to Statistical Data Analysis for the Life Sciences

Provides datasets for Introduction to Statistical Data Analysis for the Life Sciences

Datasets and functions from the (now non-existing) Faculty of Life Sciences, University of Copenhagen

Provides various functions and data sets from experiments at the Faculty of Life Sciences, University of Copenhagen. This package will be discontinued and archived, and the functions and datasets will be maintained and updated in the MESS package

Basic Functions for Power Analysis

Power analysis functions along the lines of Cohen (1988).

A Suite of Checks for Identification of Potential Errors in a Data Frame as Part of the Data Screening Process

Data screening is an important first step of any statistical analysis. dataMaid auto generates a customizable data report with a thorough summary of the checks and the results that a human can use to identify possible errors. It provides an extendable suite of test for common potential errors in a dataset.

Sequential Rank Agreement

Tools for analysing the agreement of two or more rankings of the same items. Examples are importance rankings of predictor variables and risk predictions of subjects. Benchmarks for agreement are computed based on random permutation and bootstrap.

Network Analysis and Visualization

Collection of functions for fast manipulation, handling, and analysis of large-scale networks based on family and social data. Functions are utility functions used to manipulate data in three "formats": sparse adjacency matrices, pedigree trio family data, and pedigree family data. When possible, the functions should be able to handle millions of data points quickly for use in combination with data from large public national registers and databases. Kenneth Lange (2003, ISBN:978-8181281135).

Functions for Analysis of Agreement in Method Comparison Studies

Methods (standard and advanced) for analysis of agreement between measurement methods.

Tools for Descriptive Statistics

A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'camel style' was consequently applied to functions borrowed from contributed R packages as well.

Emoji and Font Awesome in Graphics

An implementation of using emoji and fontawesome for using in both base and 'ggplot2' graphics.