Quantitative methodologies use numerical and real-world data to spot patterns and test hypotheses, which can help inform evidenced-based decisions.
CEDAR has a wide range of experience with primary and secondary data analysis, ranging from data handling and preparation, selecting methods to best fit research and evaluation questions, and undertaking small- and large-scale analysis. Our skills include:
- Data wrangling – Linking, cleaning, and preparing datasets ready for analysis, as well as assessing data quality, including accounting for missing data (e.g. multiple imputation)
- Data visualisations – Producing publication quality visualisations in Welsh and English, including advising on dashboard visualisation of routinely collected PROMs and PREMs.
- Descriptive statistics – Undertaking simple summary statistics (mean, median, count and percentage) and hypothesis testing.
- Advanced statistical analysis – Application of multivariate regression, multi-level regression, survival analysis, mediation and moderation analysis, factor and cluster analysis for cross-sectional, cohort and case-control study designs.
- Meta-analysis and network meta-analysis – Using meta-analysis and network-meta-analysis methodologies through both frequentist and Bayesian approaches, along with production of forest plot and network diagrams.
- Reporting and Dissemination – We can help interpret and disseminate findings effectively through reports, academic manuscripts, accessible infographics, conference presentations and posters.
Each project is designed within data availability constraints, and with specific timeline and budgets in mind. Our support ranges from quick data insights (e.g., summary statistics and visualisations) to robust statistical analysis, for example using routine datasets to answer specific research and evaluation questions.
We use a range of data management and analysis software including R, STATA, SPSS, SQL, and MS Excel.
All data is held confidentially in line with current information governance (IG) requirements and legislation. Identifiable, anonymised or pseudonymised data can be used. NHS service evaluation permission or proportionate ethical approval will be sought as appropriate.