Skills

The table below lists my skills in terms of the techniques I am familiar with and the software I use to implement them. They are grouped by the following areas:

  • Routine data analysis
  • Statistical analysis
  • Missing data imputation
  • Surveys and sampling
  • Evaluation methods
Area Techniques Software
Routine data analysis
  • spreadsheet modelling
  • data visualisation
  • interactive tool development
  • database development
  • data cleansing and validation
  • sensitivity analysis
  • scenario testing
  • data processing algorithms
  • simulation
  • Microsoft Excel
  • Microsoft Access
  • Microsoft Power BI
  • Visual Basic for Applications
  • SAS
  • SQL (Structured Query Language)
  • M (Power Query Language)
  • Zoho Creator & Deluge Script
Statistical analysis
  • regression modelling
  • multilevel modelling
  • event history analysis
  • factor analysis
  • latent trait analysis
  • latent class analysis
  • structural equation modelling
  • Stata
  • R
  • Mplus
  • SAS
  • SPSS
  • MLwiN
Missing data methods
  • analysis of missing data patterns
  • inverse probability weighting
  • basic imputation methods
  • expectation-maximisation imputation
  • multiple imputation using chained equations
  • Stata
  • Mplus
  • SAS
  • SPSS
Surveys and sampling
  • question design and testing
  • questionnaire design
  • web survey development
  • survey piloting and management
  • scale design
  • sample design and execution
  • power analysis
  • Lime Survey
  • MS Access
  • Visual Basic for Applications
  • Mplus
  • R
Evaluation methods
  • randomised controlled trials
  • quasi-experimental methods
  • propensity score matching
  • Stata
  • R
  • SAS