The Survey Statistician

•  Combining Survey Results http://isi.cbs.nl/iass/N62.pdf
• Small Area Estimation http://isi.cbs.nl/iass/N62.pdf
• Simple Random Sampling – for benchmarkning but not for use? http://isi.cbs.nl/iass/N58.pdf
• Analysis of complex samples in R http://isi.cbs.nl/iass/N57.pdf

The Google Public Data Explorer

• The Google Public Data Explorer makes large datasets easy to explore, visualize and communicate. As the charts and maps animate over time, the changes in the world become easier to understand. You don't have to be a data expert to navigate between different views, make your own comparisons, and share your findings.
• Google Chart Tools (Google Visualisation API)
• Google Visualization API Gallery
• Google Chart Tools / Interactive Charts (aka Visualization API)
• Quick guide to the Motion Chart Gadget
• Adding search power to public data

eBooks

eBooks

Diabetes and Obesity
Epidemiology

• Blog: R! books
• CDC: Epidemiology Training & Resources
• The CDC Field Epidemiology Manual
• CDC (2012). Principles of Epidemiology in Public Health Practice, 3rd ed.
• CDC (2015). Epidemiology and Prevention of Vaccine-Preventable Disease, "Pink book webinar series", and the pdf file of the Pink book
• Preedy (2010): Handbook of disease b burdens and quality of life measures
• Neale Batra: R for applied epidemiology and public health
• Pearl: Causal Inference in Statistics: A Primer
• Hernan (2017).Causal Inference Book
• Nick Huntington-Klein: The Effect
• Harper (2005). Methods for Measuring Cancer Disparities monograph
• Hyndman. Forecasting: principles and practice (Generating quantile forecasts in R)
• Bullard (2011). A Brief Introduction to Bayesian Statistics, Talk of NCSSM Department of Mathematics.
• Teague (2004). The Gini Index: Measuring Inequity
• O'Donnell (2008). Analyzing Health Equity Using Household Survey Data. This book used Stata doing the analyses. On the same website, there is an introduction of ADePT: Software Platform for Automated Economic Analysis, a freeware from the World Bank.
• Burton-Jeangros (2015 SpringerOpen). A life course perspective on health trajectories and transitions
• Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease by Institute of Medicine
• Social Research Methods: This website is for people involved in applied social research and evaluation. You'll find lots of resources and links to other locations on the Web that deal in applied social research methods.
• Resources of disability research
• ACS 2018: Understanding and Using American Community Survey Data: What All Data Users Need to Know
• Gary King (2004): Ecological Inference New Methodological Strategies 

Statistics

• Russell Poldrack: Statistical Thinking for the 21st Century
• Parker (2017).National Center for Health Statistics Data Presentation Standards for Proportions
• Huff (1954). How to lie with statistics
• Free Statistics book collected by FreeTechBooks
• Hyndman & Athanasopolos. Forecasting: principles and practice (book notes) (using R!)
• Swinscow. Statistics at Square One - BMJ
• Cosma Shalizi: Advanced Data Analysis from an Elementary Point of View
• Lance (2014). How do we know if a prog4ram made a difference? A guide to statistical methods for program impact evaluation (using Stata) (pdf)
• Norm Matloff:From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science (R!)
• Shalizi (2016).Advanced Data Analysis from an Elementary Point of View (draft)
• Stephen Jenkins. Survival Analysis with Stata - University of Essex
• IARC Scientific Publication (Selected)
• Breslow (1980): Statistical Methods in Cancer Research Volume I: The Analysis of Case-Control Studies
• Breslow (1986): Statistical Methods in Cancer Research Volume II: The Design and Analysis of Cohort Studies
• Krewski (1986): Statistical Methods in Cancer Research Volume III: The Design and Analysis of Long-term Animal Experiments
• Esteve (1994): Statistical Methods in Cancer Research Volume IV: Descriptive Epidemiology
• Gary Oehlert (2010).A First Course in Design and Analysis of Experiments
• Statistics in Medicine: Tutorial papers from Statistics in Medicine for FREE (before 12/31/17)
• Statsoft
• Engineering Statistics Handbook
• Reliability Engineering Resource Web Site
• Analytic Methods in Maternal and Child Health has a chapter about Methods for Analyzing Trend Data
• Train (2002). Discrete Choice Methods with Simulation (pdf), which is referred by Luedicke in "Flexible discrete choice modeling using a multinomial probit model" using Stata. A blog about Discrete Choice Analysis and a Wikipedia article
• Kuhfeld. Discrete Choice (pdf)  using SAS [discrete choice analysis is a statistical technique for modeling trade-offs such as consumers make between the features and the price of a good or service. Results of this analysis indicate what features may be added, eliminated, or enhanced, and how the different versions of the same item may sold at different price levels.]
• Simon Wood: Core Statistics (pdf) for anyone starting a statistics PhD
• HyperStat Online: An introductory statistics textbook and online tutorial for help in statistics courses
• AP Statistics Curriculum 2007
• CurveFit: a guideline of nonlinear regression in GraphPad library.
• National Guideline Clearinghouse
• IARC Publications - there are a few good books about statistical methods
• Berger (1988). The likelihood principle: a review, generalizations, and statistical implications (from Institute of Mathematical Statistics Lecture Notes - Monograph Series (free) on Euclid)
• Sgro: Tabular data analysis with R and Tidyverse (How to Use Survey Weights in R by Mike Burke)
• Open Textbook Library supported by the Center for Open Education and the Open Textbook Network
• Diez (2004): Introductory Statistics with Randomization and Simulation 1st
• Blais (2017): Statistical Inference for Everyone

Data Science

• Boehmke: Hands-On Machine Learning with R (Interpretable Machine Learning)
• Molnar (2021): Interpretable Machine Learning - A Guide for Making Black Box Models Explainable
• Burkov: Machine Learning Engineering
• Burkov: The Hundred-Page Machine Learning Book
• Peng: R Programming for Data Science
• Max Welling (2011). A First Encounter with Machine Learning
• Efron & Hastie (2016): Computer Age Statistical Inference: Algorithms, Evidence and Data Science
• Pear (2018): The Seven Pillars of Causal Reasoning with Reflections on Machine Learning
• Gareth James (2013), Trevor Hastie, Robert Tibshirani, Daniela Witten: An Introduction to Statistical Learning, with Applications in R, 2nd. pdf) with the excellent self-paced video training course. (here is the 15-hours of video training video abstracted by the Data School (YouTube))
• Trevor Hastie (2009): The Elements of Statistical Learning: Data Mining, Inference, and Prediction. This book is not an easy read book without strong mathematical knowledge.
• Ian Goodfellow: Deep Learning - a MIT Press book
• Deisenroth (2020):Mathematics for Machine Learning
• Bishop (2006): Pattern Recognition and Machine Learning
• Barber. Bayesian Reasoning and Machine Learning. This is a book for a person with little background in math and probabilistic methods.
• John Paisley (2016): Course notes for Bayesian models for machine learning 
• Bernhard Scholkopf (2019): Causality for machine learning
• Blum: Foundations of Data Science
• Silge: Text Mining with R
• Kroese: Data Science & Machine Learning: Mathematical and Statistical Methods (Python)
• Introduction to Earth Data Science (Python) Jupyter For Python (Code and Markdown)
• R Interface to Python (reticulate)
• Monarch: Human-in-the-Loop Machine Learning

Mathematics

• Grinstead: Introduction to Probability
• Pishro-Nik (2014): Introduction to Probability, Statistics, and Random Processes (video)
• Thompson(1914): Calculus Made Easy, 2nd, Project Gutenberg version
• Strang (1991). Calculus (MIT)
• Boyd: Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares
• 3Blue1Brown: Essence of mathematics
• Hefferon: Linear Algebra
• Mathews (1991): Elementary Linear Algebra
• A First Course in Linear Algebra
• Wilke: Fundamentals of Data Visualization from the Serial Mentor

Econometrics

• Bruce Hansen: Introduction to Econometrics and Econometrics
• Hanck: Introduction to Econometrics with R (pdf)
• Colonescu: Principles of Econometrics with R (pdf)
• Robinson: 10 Fundamental Theorems for Econometrics (Delta Method in Plain English)

Others

• CDC Crisis & Emergency Risk Communication Manual and Tools
• FreeTechBooks: more related to computer science, engineering and programming 
• LibriVox, the free public domain audiobooks
• Schulz. Why using the greedy.* in regular expression is almost never what you actually want
• The art of scientific investigation (1957)
• Free Kindle book updates
• Free eBook Collections - Free classics and out-of-copyright, pre-1923 books, as well as limited-time free promotional ebooks available for Kindle.
• Free Kindle Books offers Free Classic E-Books in Kindle-compatible MOBI and PRC formats.
• Project Gutenberg is the place where you can download over 33,000 free ebooks to read on your PC, iPad, Kindle, Sony Reader, iPhone, Android or other portable device.
• ManyBooks.net There are more than 29,000 eBooks available here and they're all free!
• FreeBookSpot FreeBookSpot is an online source of free ebooks download with 4485 FREE E-BOOKS in 96 categories
• BookYards is a web portal in which books, education materials, information, and content will be freely to anyone who has an internet connection.
• Free Ebook (need register as a member)
• Apprentice Alf's Blog about DRM. Online eBook Converter

中文 (Chinese)

• 喜马拉雅FM 提供海量有声内容
• HaoDoo: 好讀網站不是實體書出版社，而是一個推廣中文電子書的公益網站。好讀網站免費提供: 1) 好讀中文直式閱讀軟體; 2) 好讀製書程式 mPDB﹙您可自行製書﹚; 3) 好讀書櫃﹙整理校正過的好書﹚
• 书仓网 - 还你阅读的自由与惬意 ePub、mobi、pdf、在线阅读、手机阅读、电子书
• 读书频道 - 腾讯网
• 久久小说下载网 (TXT电子书)
• 落吧电子书下载网 (TXT电子书)
• 亦凡公益图书馆

Oral Diabetes Medications for Adults with Diabetes: An Update

Key Question 1: In adults age 18 or older with type 2 diabetes mellitus, what is the comparative effectiveness of these treatment options (see list of comparisons) for the intermediate outcomes of glycemic control (in terms of HbA1c), weight, or lipids?

Key Question 2: In adults age 18 or older with type 2 diabetes mellitus, what is the comparative effectiveness of the treatment options (see list of comparisons) in terms of the following long-term clinical outcomes?

Key Question 3: In adults age 18 or older with type 2 diabetes mellitus, what is the comparative safety of the treatment options (see list of comparisons) in terms of the following adverse events and side effects?

Key Question 4: Do the safety and effectiveness of these treatment options (see list of comparisons) differ across subgroups of adults with type 2 diabetes, in particular for adults age 65 or older, in terms of mortality, hypoglycemia, cardiovascular, and cerebrovascular outcomes?

Popularity of Data Analysis Software Revisited

Thank you Bob for this article nicely compared the popularity of analytical software. I’m using SAS, Stata, and R mostly. Personally I treat SAS a product of a IBM-kind company, Stata as a  product of a Apple-kind company, and R as a product of a Google-kind company. 

How to Print Large Posters Using Freeware

The PosteRazor cuts a raster image into pieces which can afterwards be printed out and assembled to a poster. As input, the PosteRazor takes a raster image. The resulting poster is saved as a multipage PDF document. An easy to use, wizard like user interface guides through 5 steps. PosteRazor is available as a Windows, an OSX and a Linux version.

The Rasterbator is very easy to use. You can either upload a file from your computer or use any file that is publicly available in the Internet. After you have cropped the image and selected a desired size, the rasterbated image will be sent to you as an easily printable pdf file.  

Use POSTERIZA to design your own big posters and signs from any digital photo with your home printer! 

EpiWonk: an epidemiology Blog

Journal: Significance

Significance is a quarterly magazine for anyone interested in statistics and the analysis and interpretation of data. Its aim is to communicate and demonstrate in an entertaining, thought-provoking and non-technical way the practical use of statistics in all walks of life and to show informatively and authoritatively how statistics benefit society.

• Bradley Efron and Efron’s bootstrap (2010), Statistical inference using bootstrap confidence intervals (2004)
• Introduction to Markov chains – the finite case (2010)
• Bayes factors (2006), Bayesian thought (2004), Statistics and the Bayesianmind (2007)
• Does significance matter? (2004)
• Making information beautiful – and clear (2011)
• The t-test tool (2008)
• Becoming familiar with multilevel modeling (2007)

Journal: Statistics Science

On this site, there are many quite knowledgeable articles and interviews:

• The Bootstrap and Bradley Efron: A Conversation with Good Friends (2003); Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Accuracy (1986)
• Understanding the shape of the hazard rate (2001)
• How to Lie with Statistics Turns Fifty (2005)
• The Bayes (2004)
• Struggles with Survey Weighting and Regression Modeling (2007)
• Statistics and the Environment (2003)
• Tribute to John W. Tukey (2003), A conversation with John W. Tukey and Elizabeth Tukey (2000)
• Voting, elections, and statistical science (2002)
• A Conversation with Chin Long Chiang (1999)
• Regression Models for Adjusting the 1980 Census (1986)
• The Central Limit Theorem Around 1935 (1986)

R Resources/Tips

• R Project website, R-Forge
• R Seek: R-project Search Engine; R Search: Original Search Engine by R Project

• R Blog:
• R-Bloggers: R news and tutorials.
• inside-R  A Community Site for R sponsored by Revolution Analytics.
• R-Statistics

• Graphical User Interface (GUI): 
• RStudio: my favorite integrated development environment (IDE) for R. Usually I run R from the RStudio.
• Rcmdr (R Commander): my favorite GUI.
• Deducer: Another R GUI.
• Sciviews R Wiki; Wikipedia R Wiki
• R graphic gallery
• ggplot2: a plotting system for R, based on the grammar of graphics. There is a free ggplot2 webinar from Hadley Wickham.
• R Programming; R Inferno pdf 
• Tip: how to start a package at the start-up of R

MultiLevel Models for Complex Survey Data

at BRFSS Conference

March 19, 2011

Alan Hubbard hubbard@berkeley.edu
UC Berkeley, School of Public Health, Div. of Biostatistics

The statistical analysis of interval-censored failure time data By Jianguo Sun

The statistical analysis of interval-censored failure time data

 By Jianguo Sun

A Google book, here

How to Load R Package At Start-up of R

If you wish to load Deducer every time you start R, open Rprofile.site with notepad. It should be located in the directory: "C:\Program Files\R\R-x.x.x\etc\", then add:

local({

old <- getOption("defaultPackages")

options(defaultPackages = c(old, "Deducer","DeducerExtras"))

})

Excess mortality in osteoarthritis -- Cooper and Arden 342 -- bmj.com

Excess mortality in osteoarthritis

  -- Cooper and Arden 342 -- bmj.com

http://www.bmj.com/content/342/bmj.d1407.extract?etoc

Role of Environmental Chemicals in the Development of Diabetes and Obesity

Workshop Presentations Tuesday - January 11, 2011 Introductions, Overview, and Charge - Dr. Michael Gallo Workshop format and process to develop and finalize the NTP monograph - Dr. Kristina Thayer Bioinformatics and high throughput screening (HTS) Breakout Group Presentations: “Overview of the Tox21 collaboration” – Dr. Ray Tice “Training session to learn how to access Tox21 data”– Dr. Richard Judson “Demo of the NIH Chemical Genomics Center (NCGC) Human Pathway Universe” – presented by Dr. Ray Tice on behalf of Dr. Ruili Huang Wednesday - January 12, 2011 Breakout Group Report: Organotins and phthalates - Dr. Kim Boekelheide Breakout Group Report: BPA, steriod hormones and thyroid hormones - Dr. Ted Schettler Breakout Group Report: Nicotine and pesticides - Dr. Allison Holloway Breakout Group Report: Arsenic and other metals - Dr. Dana Loomis Breakout Group Report: Persistent Organic Pollutants (POPs) - Dr. Raymond Novak Breakout Group Report: Bioinformartics and HTS approaches - William Janzen Plenary lecture: "An environmental-wide association study on Type 2 diabetes mellitus" - Chirag Patel Thursday - January 13, 2011 Research Strategies and Critical Data Needs: Common Themes - Dr. Michael Gallo Research Strategies and Key Data Needs (Breakout Group A) - Dr. Franck Mauvais-Jarvis Research Strategies and Key Data Needs (Breakout Group B) - Dr. Morris White Research Strategies and Key Data Needs (Breakout Group C) - Dr. Lars Lind Research Strategies and Key Data Needs (Breakout Group D) - Dr. James Kaput General Discussion: Comments by Dr. David Jacobs Closing Comments - Dr. Michael Gallo

中美家教调查：虎妈PK猫爸差异大 虎妈至多只成功50

中美家教调查：虎妈PK猫爸差异大 虎妈至多只成功50

http://news.backchina.com/viewnews-128246-gb2312.html

Atlas of United States Mortality

Atlas of United States Mortality

http://www.cdc.gov/nchs/products/other/atlas/atlas.htm

2010 Surgeon General's Report—How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

http://www.cdc.gov/tobacco/data_statistics/sgr/2010/index.htm

Thinking styles: deductive or inductive?
Source: Body Language Cards

Deductive reasoning is learning about data from theory and the model. Inductive reasoning is learning about the theory and the model from a study of the data.

People in cultures with a deductive thinking style are comfortable with abstractions. In an argument, discussion or written presentation, they prefer to go from the general to the specific and to deduce facts from general principles.

In cultures with an inductive thinking style, people go from the specific to the general. They arrive at a theory or model only after amassing facts through experimentation and observation.
The French (and Chinese), for example, tend to be highly deductive. North Americans, particularly US Americans, tend to be highly inductive.
Other Sources:
Research Methods Knowledge Base

Wiki article about reasoning
Stephen's Guide to the Logical Fallacies

  

USDA Dietary Guidelines for Americans, 2010
http://www.cnpp.usda.gov/DGAs2010-PolicyDocument.htm