Effective research support involves more than running statistical software. It starts with understanding the study objectives and checking the data, then ends with results that can be written and discussed confidently.
Reviewing objectives and data
The process begins with the research questions, hypotheses, dataset, and questionnaire structure. This review can reveal coding problems and missing values and establish each variable's measurement level before tests are selected.
Support for questionnaire studies
Support may include coding responses, reviewing reverse-scored items, calculating scale scores, preparing demographic tables, assessing reliability such as Cronbach's alpha, and choosing comparisons aligned with the study objectives.
Support for medical and health research
Clinical variables and patient characteristics can be organized, unusual values reviewed, groups compared, and risk factors or relationships between measurements examined, with both significant and nonsignificant findings reported clearly.
Selecting analyses and tools
Methods are selected according to variable types, sample size, study design, and statistical assumptions. SPSS is used primarily, while jamovi, Python, or Power BI may be used when they suit the data and required outputs.
Interpreting and preparing outputs
Support continues beyond tables by connecting results to the research objectives and explaining p-values, effect sizes, associations, and regression models. Tables and charts are organized to support the results chapter and discussions with supervisors or collaborators.
Need help analyzing your data?
Send your research objectives and data file for clear guidance on a suitable analysis.
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