Quantitative consulting service
Check whether your measures support the conclusions you want to make
Check whether items and scales support the inferences that later models are expected to carry.
Question→Design→Data→Model→Diagnostics→Interpretation
When this support is useful
When a survey, instrument, latent construct, or score needs scrutiny before outcome modeling.
- Does the measure behave as intended?
- Is factor analysis warranted?
- Is the same construct measured across groups?
How the decision is approached
The workflow starts with the research question and data-generating structure. Methods and software follow from that logic, with assumptions, alternatives, and failure modes recorded before conclusions are polished.
- Item screening and reliability
- EFA and CFA
- Invariance and Rasch/IRT where appropriate
What a defensible handover can include
Deliverables are agreed to fit the decision and the people who must review or continue the work. They are not a fixed bundle of software output.
- Measurement decision log
- Factor-analysis summary
- Validity limitations
Start with the decision
Discuss this statistical decision
Bring the research question, design, or existing output. A first review can identify the next statistical decision and the information needed to scope it.