At MDR, we transform raw data into meaningful information that informs public policy, program design, and service delivery. Our standard analyses include descriptive statistics such as frequencies and cross-tabulations by key demographic and respondent characteristics. When greater precision is needed, we provide weighted population estimates, percentages, standard errors, and confidence intervals.

For projects that demand deeper insight, MDR’s analysts apply a broad range of advanced statistical techniques. Our team is experienced in both the design and interpretation of multivariate methods that uncover patterns, identify predictive factors, and optimize decisions.

Predictive Modeling
We use linear, logistic, and other regression models to identify which variables most strongly predict an outcome and to quantify their relative influence. These models support scenario testing, forecasting, and evidence-based decision-making in fields ranging from health outcomes to service utilization.

Population and Demographic Forecasting
MDR develops short- and long-term projections based on demographic trends, migration patterns, birth rates, and other social determinants. These forecasts help agencies and organizations plan for future service needs, infrastructure investment, and workforce development.

Economic Analysis
We conduct cost analyses, economic impact studies, and return-on-investment modeling to assess the fiscal implications of programs, policies, and services. Our work supports budget planning, policy evaluation, and funding advocacy.

Multidimensional Scaling (MDS) / Perceptual Mapping
MDS visually maps how respondents perceive similarities and differences among brands, institutions, or services. By measuring perceived distances between items based on key attributes (e.g., quality, cost), we create intuitive visualizations that inform positioning strategies and stakeholder engagement.

Cluster Analysis
Cluster analysis segments respondents into distinct groups based on shared attitudes, behaviors, or demographics. These insights support targeted messaging, resource allocation, and tailored interventions.

Discrete Choice and Conjoint Analysis
These methods identify which product or service attributes matter most to users. By presenting respondents with choices between different combinations of features, we model preference structures, estimate demand, and determine the optimal mix of features to maximize appeal or value.

MDR tailors each analytic approach to the needs of the project, ensuring findings are not only statistically valid but also actionable and accessible to stakeholders.