Methodology

This area of the website contains relates to methodology, research design, and analysis.

Any suggestions then please let me know, especially if you’d like to add to the list of potentially links that I’m (slowly) collecting below:

Data visualisation

Slides on visual rhetoric and ‘improving your image’

Sites with examples of analysis using different methods and software packages

Survey design and analysis

Statistics Canada: Planning a survey
Statistics Canada: Sample selection (e.g. target population and sample frame)
Statistics Canada: Sample design (e.g. clustering and stratification)
Groves and Lyberg (2010) Total survey error: Past, present, and future
Missingdata.org.uk (a site dedicated to missing data)
Johns Hopkins: Issues in survey research design (open course with lecture materials)
Johns Hopkins: Statistical methods for sample surveys (open course with lecture materials)
Johns Hopkins: Simple random sampling with and without replacement
Survey analysis in Stata using ‘svy’ (an example)
Create survey weights in Stata using ‘ipfweight’ or ‘ipfraking’
Survey analysis in R using the ‘survey’ package (can also be used to create weights)
Introduction to power analysis (UCLA)
Choosing the sample size for a survey (tools for development)

Event history, survival analysis, and multilevel models

Event history analysis (very clear overview of the method by Fiona Steele)
Survival analysis with Stata (course notes by Stephen Jenkins)
Survival analysis with R (book and materials by Melinda Mills)
The Cox model: introduction and history (Bianca De Stavola)
Multilevel modelling: online training (Bristol)

Evaluation and causal inference

General statistical methods

Statement on p-values (American Statistical Association)

Software: R

Quick R
Short list of R commands
R tutorial
Wikibooks: R programming
iNZight (front end for teaching and learning statistics using R)

Software: Stata

Text editors for statistical programming

Tex resources