Analysis planning
Questions, variables, assumptions, missing data, estimands, models, and transparent decision rules.
Quantitative analysis and measurement
Make the data answer the right question.
MCRC Health helps organizations strengthen measures, analyze data, and communicate results without overstating what the design can support.
Capabilities
Analysis with the decision and design in view.
Statistical analysis
Descriptive, comparative, regression, repeated-measures, and other fit-for-purpose approaches.
Survey and measurement
Questionnaire design, measure selection, reliability, validity, scoring, and respondent burden.
Performance reporting
Indicators, dashboards, visualizations, interpretation, limitations, and decision-focused reporting.
Direct answer
What does quantitative analysis include?
Quantitative analysis can include data cleaning, descriptive statistics, measurement assessment, group comparisons, regression or longitudinal models, sensitivity analyses, visualization, and interpretation.
The appropriate methods depend on the research or evaluation question, design, sample, measurement quality, missingness, assumptions, and decisions the results will inform.
Typical work
From raw data to useful interpretation.
Existing datasets
Assess structure and quality, refine questions, analyze, and document limitations.
Surveys
Design instruments, choose measures, plan sampling, and interpret responses.
Program data
Develop meaningful indicators and examine reach, variation, change, and outcomes.
Research outputs
Analysis plans, tables, figures, reports, manuscripts, and presentations.
Questions
Quantitative support, in practical terms.
Can you analyze an existing dataset?
Yes. We can assess data quality and structure, refine the questions, develop an analysis plan, conduct the analysis, document limitations, and translate the results for the intended audience.
Can you build a dashboard?
Yes, when a dashboard is the right reporting tool. We first define the audience, decisions, indicators, data flow, update cadence, and interpretation needed so the dashboard remains useful rather than merely visual.
Can you help choose outcome measures?
Yes. Measure selection can consider validity, reliability, responsiveness, feasibility, licensing, equity, respondent burden, comparability, and fit with the intended decision.
Have data but need a clearer answer?
Share the question, dataset, intended audience, and timeline—even if the analysis plan is not yet defined.
Discuss the analysis