Effect of population screening for type 2 diabetes
by Medical Xpress August 24, 2017
"Three large trials published today in Diabetologia (the journal of the European Association for the Study of Diabetes) show that screening for type 2 diabetes and cardiovascular risk factors may not reduce mortality and cardiovascular disease in the general population. However, for individuals diagnosed with diabetes, screening is associated with a reduction in mortality and cardiovascular disease risk. " full text
Articles mentioned in this news:
Continuing Professional Education & Glossary by JECH
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How to estimate the risk and relative risk from logistic regression of a case-control study (OR to RR)
One advantage of odds ratios is that we can estimate it in a case-control study, when we usually oversample the cases. However, we cannot directly calculate the probability using logistic regression in a case-control study, since the beta(0) of the case-control study cannot represent the target population, which beta(0) of the target population is equal to beta(0) of the case-control study - log(sampling probability for cases/sampling probability for controls)
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R! related
Blog: R Documentation and Learning Resources
IDE and GUI
- RStudio is an IDE for R. RStudio combines an intuitive user interface with powerful coding tools to help you get the most out of R. RStudio Webinars
- Rcmdr is a GUI of R.
- esquisse is a great addin for ggplot2
- Deducer is a good but relative old GUI for exploring data like JMP with ggplot2 behind (Plot Builder). JGR is a Java GUI for R. (ggplot2 – much easier with JGR and Deducer). To use Deducer, you need - install.packages(c("JGR", "Deducer", "DeducerExtras")) -, submit: - library(JGR) -, - JGR() -; then, in the JGR console, to load Deducer, go to 'Packages & Data' > 'Package Manager' and select Deducer and DeducerExtras. more: all-in-one installing JGR and Deducer. Notes: 1) to set JAVA location using --- options(java.home="xxx/Java/") ---. 2) rJAVA ver 9.6 needs running under the 32 bit R! on my computers.
- GrapheR (pdf) is another GUI for draw customized graphs without knowing any R commands.
- Tessera - Open source environment for deep analysis of large complex data (Divide and recombine）
- The application Bio7 is an integrated development environment for ecological modelling and contains powerful tools for model creation, scientific image analysis (ImageJ) and statistical analysis.
Communication between SAS and R
Graphical parameters
R! How can I include Greek letters in my plot labels?
Revolutions: How to make a heat map in R, Superheat: supercharged heatmaps for R
Chart Chooser — improves Excel and PowerPoint charts. there is R! version of Chart Chooser (not many charts on the site, but the idea is great)
Packages (rdrr.io, CRAN, Rdocumentation, Inside-R, Quick-R, Bioconductor)
- CRAN Task View organizes the packages into different groups such as Graphics, Survival Analysis, etc.
- margins: An introduction to 'margins'
- Transition from Excel to R!:
- DT: An R interface to the DataTables library
- excelR: An R interface to jExcel library to create web-based interactive tables and spreadsheets compatible with Excel or any other spreadsheet software
- DTedit: Editable DataTables for shiny apps
- rhandsontable is a htmlwidget based on the handsontable.js library.
- formattable is designed for applying formatting on vectors and data frames
- rpivotTable is a R wrapper for the great library pivottable
- Zelig is a general purpose statistics program fro estimating, interpreting, and presenting results from any statistical method. It turns the power of R with free ranging syntax, diverse examples, and documentation written for different audiences — into the same three commands and consistent documentation for every method
- Report and documentation
- knitr package was designed to generate dynamic report with R. Chunk options.
- rmarkdown is an authoring format that enables easy creation of dynamic documents, presentations, and reports from R.
- bookdown is to facilitate writing books and long-form articles/reports with R Markdown. Here are several very good free books published on the bookdown website
- Programming
- Devtools makes it so easy to build a package that it becomes your default way to organise code, data and documentation.
- Data I/O and manipulation
- haven allows you to load foreign data formats (SAS, SPSS and Stata).
- xlsx gives programatic control of Excel files using R.
- read.table() reads a file in table format and creates a data frame from it.
- arrow supports for analyzing large, multi-file datasets, working with individual Parquet and Feather files.
- MMWRweek: Convert dates to MMWR Day, Week, and Year
- dlookr: Diagnose, explore and transform data
- foreign read data stored by other system.
- dplyr is a new package which provides a set of tools for efficiently manipulating datasets in R. Introduction to dplyr. Notes: "Both data.table and dplyr were able to reduce the problem to less than a few seconds. If you’re looking for pure speed data.table is the clear winner. However, it is my understanding that data.table‘s syntax can be frustrating, so if you’re already used to the ‘Hadley ecosystem’ of packages, dplyr is a formitable alternative, even if it is still in the early stages."
- tidyr with spread() and gather(), a reframing of reshape2, is a new package that makes it easy to “tidy” your data.
- magrittr is a forward pipe operator. magrittr: Simplifying R code with pipes. History of Magrittr.
- Aggregation and restructure: reshape2 package with melt() or cast() function.Transpose using t() function, aggregating data using aggregate() function.
- lubridate is good for manipulating time and date.
- Stringr makes it easier to work with strings (article).
- Quick-R examples of outputing R data.
- RStudio addins: datapasta, ggthemeassist
- pdftools: Text Extraction, Rendering and Converting of PDF Documents (example)
- Survey related packages
- GIS
- Data Visualization and Graphics
- ggplot2 (document) (You can build the book here: ggplot2: Elegant graphics for data analysis) is a plotting system for R, based on the grammar of graphics, which tries to take the good parts of base and lattice graphics and none of the bad parts. Cookbook for R is a great book. Tutorial websites: Tutorial I, Tutorial II. A good book website of Guide to Create Beautiful Graphics in R (Cheatsheet: Be Awesome in ggplot2). Beautiful plotting in R: A ggplot2 cheatsheet (pdf). Tutorial video (Part I and Part II) by Roger Peng
- A conversation with Hadley Wickham 2014 - Eduardo
- ggthemes is a package including some extra geoms, scales, and themes styles (the Economist, Excel, Stata, etc.) for ggplot2.
- GGally is designed to be a helper to ggplot2. It contains templates for different plots to be combined into a plot matrix, a parallel coordinate plot function, as well as a function for making a network plot.
- gtable is a package of tools to make it easier to work with ``tables'' of grobs, which is internally used by ggplot2. I used the gtable::cbind(..., size = "max", z = NULL) or gtable::rbind(..., size = "max", z = NULL) to match the size of plots.
- ggprepel is a ggplot2 extension to avoid overlapping text labels.
- Walker (2014). International population pyramids with ggplot2
- ggforce accelerates 'ggplot2'
- ggraph is an extension of ggplot2 tailored at plotting graph-like data structures (graphs, networks, trees, hierarchies...)
- WVPlots Provides examples of ggplot plots that can be generated from a standard calling interface
- classifierplots generates a visualization of binary classifier performance as a grid of diagonstic plots with just one function call
- ggalt: amke a dumbbell plot in ggplot2
- ggcharts aims to get you to your desired plot faster.
- Plotly: ggplotly of plotly package is a powerful tool to convert ggplot2 plots and create interactive, online ggplot2 charts with D3.js. Carson Sievert used this converter recreated Hadley Wickam’s entire ggplot2 documentation (here). Click-drag to zoom, shift-click to pan, double-click to autoscale. It's really amazing. Plotly Tutorial: Plotly and R
- grid and gridExtra are useful combined with ggplot2, for example:
- ggvis new package for data visualization. Like ggplot2, it is built on concepts from the grammar of graphics, but it also adds interactivity, a new data pipeline, and it renders in a web browser.
- vcd for visualizing categorical data. Working with categorical data with R and the vcd and vcdExtra packages and Visualizing Categorical Data with SAS and R by Michael Friendly.
- Distribution visualization: vioplot for violin plot (examples of boxplot and violin plot). Hintze (1998). Violin Plots: A Box Plot-Density Trace Synergism. Violin plot using ggplot2. Boxplots and beyond: Part I, II: asymmetry, III: violin plots, IV: beanplots.
- venneuler is my favorite package for make a area proportional Venn and Euler Diagram simple and fast, I use it create diagrams then use Inkscape to modify them. A more complicated package is VennDiagram. Wilkinson (2012) introduced his venneuler package in the artilce "Exact and Approximate Area-proportional Circular Venn and EulerDiagrams". Chen (2011) compared some R! package and programs in the article "VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R" (Create a Venn diagram using MS Excel)
- venn = venneuler(c(a1c=.15, fpg=.11, ogtt=.13, 'a1c&fpg'=.1, 'fpg&ogtt'=.13, 'a1c&ogtt'=.4, 'a1c&ogtt&unknow'=.1))
- plot(venn)
- Vennerable package provides routines to compute and plot Venn diagrams, including the classic two- and three-circle diagrams but also a variety of others with different properties such as rectangular or square Venn diagram and for up to seven sets. It's not available at CRAN. You can install this package using: install.packages("Vennerable", repos = "http://R-Forge.R-project.org")
- googleVis - Google Motion Charts with R!
- colourlovers provides access to the COLOURlovers API, which offers color inspiration and color palettes
- Lattice is a powerful and elegant high-level data visualization system, with an emphasis on multivariate data.
- scatterplot3d provides routines for the visualization of multivariate data in a three dimensional space.
- iPlots is a package for the R! which provides high interaction statistical graphics, written in Java.
- rcharts is an R package to create, customize and publish interactive javascript visualizations from R using a familiar lattice style plotting interface.
- wordcloud2 and wordcloud create wordcloud for data visualization. Using R to create a Word Cloud from a PDF Document. 可能是目前最好的词云解决方案wordcloud2
- David Smith (2017).Packages to simplify mapping in R
- magick is a package of wrapping up of ImageMagick which is an image processing library
- networkD3: D3 JavaScript Network Graphs from R, good at Sankey Diagram
- Missing Imputation
- Statistics/Machine Learning
- MLR – Machine Learning in R and MLR3 a scussor of MLR. Here is the mlr3 book
- tidymodes: a combination of multiple packages: parsnip, recipes, etc.
- tidyverse is a collection of popular packages for data munging from Hadley Wickham including ggplot2, dplyr, tidyr, readr, purrr, tibble, etc.
- bayestestR provides a comprehensive and consistent set of functions to analyze and describe posterior distributions generated by a variety of models objects, including popular modeling packages such as rstanarm, brms or BayesFactor.
- rms: is a package goes along with the book Regression Modeling Strategies
- caret is a set of functions that attempt to streamline the process for creating predictive models. Here are caret webinar and slides
- splines is now a part of R! standard/add-on packages/bundle. splines::ns() generate a matrix for natural cubic splines. Bendix tuned the ns() as Ns() in his Epi package, which used the smallest and the largest of the supplied knots as boundary knots. You can download the latest version on his website here.
- lavaan: latent variable analysis
- msm::deltamethod: delta method, FAQ UCLA
- nls can be used to determine the nonlinear (weighted) least-squares estimates of the parameters of a nonlinear model, which is similar to the 'nl' of stata and 'proc nlin' of SAS
- rpart is for the recursive partitioning for classification, regression and survival trees.
- Hmisc: Harrell Miscellaneous
- convey estimates measures of poverty, inequality, and wellbeing using the complex survey data
- deltavar() is a function in the emdbook packages of the book, which calculates delta-method-based variances for functions with any number of parameters
- deltavar(log(A/B),meanval=c(A=0.8,B=12),Sigma=matrix(c(0.1,0,0,8.0),nrow=2)) ---> 0.2118056 = ((1/A)^2*Var(A)+(1/B)^2*Var(B))^0.5
- deltavar(log(A/B),meanval=c(A=0.8,B=12),Sigma=c(0.1,8.0)) -> 0.2118056
- MASS is a classic package for Venables and Ripley's Modern Applied Statistics with S
- Bolstad is A set of R functions and data sets for the book Introduction to Bayesian Statistics, Bolstad, W.M. (2016). The "bayes.lin.reg" function may be used for combining the two estimates like meta-analysis.
- Psych: Using R for psychological research
- Electronic Health/Medical Record (EHR) related
- coder: Deterministic Categorization of Items Based on External Code Data by rOpenSci (blog)
