Discrete Choice Experiment Consulting

Understanding what drives decision-making is fundamental to effective product development, policy design, and market research.

As a specialized discrete choice modeling consultant, I help you uncover the underlying preferences that shape consumer, patient, and stakeholder choices through rigorous experimental design and advanced choice modeling techniques.

Whether you’re developing new products, evaluating policy options, or conducting health economics research, my expertise ensures your choice experiments deliver actionable insights with statistical precision.

Comprehensive Discrete Choice Experiment Services

Transform complex decision-making questions into clear preference insights.

My end-to-end DCE services help researchers and organizations understand how people make choices when faced with multiple options and trade-offs.

Experimental Design & Choice Set Development

Create statistically efficient choice experiments that maximize information while minimizing respondent burden.

  • Design orthogonal and D-efficient choice sets with optimal attribute level combinations
  • Develop realistic hypothetical scenarios that reflect real-world decision contexts
  • Create balanced choice arrays that capture main effects and two-factor interactions
  • Determine appropriate sample sizes through power analysis and simulation
  • Implement blocking strategies to manage complex experimental designs
  • Design pilot studies to refine attributes and test choice experiment feasibility

Survey Design & Implementation

Build engaging choice experiments that capture authentic preferences.

  • Develop scenario-based surveys with clear attribute descriptions
  • Create intuitive choice interfaces that minimize cognitive burden
  • Design effective warm-up and practice scenarios for respondent training
  • Implement quality control measures and attention checks
  • Conduct pre-testing and cognitive interviews to validate survey instruments
  • Manage data collection across multiple platforms and populations

Advanced Choice Modeling & Analysis

Apply sophisticated statistical methods to extract meaningful preference insights.

  • Implement multinomial logit models and mixed logit specifications
  • Conduct utility estimation and preference parameter calculations
  • Analyze preference heterogeneity across respondent segments
  • Perform willingness-to-pay calculations and value assessments
  • Test alternative-specific constants and choice context effects
  • Apply behavioral choice modeling techniques including matching law approaches

Health Economics & Patient Preference Applications

Specialized expertise in healthcare choice experiments and preference elicitation.

  • Design patient preference studies for treatment and care pathway evaluation
  • Conduct benefit-risk assessments for pharmaceutical and medical device research
  • Perform health technology assessment studies with preference-based outcomes
  • Analyze healthcare provider and payer decision-making processes
  • Support regulatory submissions requiring patient preference evidence
  • Evaluate health policy interventions through stated preference methods

Market Research & Business Applications

Translate choice experiment results into strategic business insights.

  • Conduct product feature optimization through attribute-based choice analysis
  • Perform market segmentation based on preference patterns
  • Evaluate pricing strategies through willingness-to-pay estimation
  • Analyze competitive positioning through choice share simulation
  • Support new product development with preference-driven design decisions
  • Assess policy impact through scenario analysis and choice modeling

Results Interpretation & Decision Support

Convert complex choice modeling results into actionable recommendations.

  • Generate clear preference rankings and importance weights
  • Create market simulation models for scenario planning
  • Develop decision trees and preference-based algorithms
  • Produce publication-ready results with appropriate statistical reporting
  • Provide strategic recommendations based on choice experiment findings
  • Support implementation planning with preference-informed decision frameworks
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Why Work With Me For Your Discrete Choice Experiments?

Working with a DCE specialist benefits you in multiple ways.

Methodological Expertise

Access proven choice modeling techniques refined through years of specialized practice.

Efficient Project Delivery

Focus on your core research questions while I handle the technical complexities of choice experiment design and analysis.

Robust Statistical Approach

Benefit from advanced modeling techniques that capture preference heterogeneity and choice context effects with statistical rigor.

Actionable Insights

Receive clear preference insights that directly inform decision-making, whether for product development, policy design, or strategic planning.

The Discrete Choice Experiment Process

My DCE consulting process ensures methodological rigor and practical applicability.

Research Design Phase

We discuss your decision-making questions, identify key choice attributes, and determine the most appropriate experimental approach for your context and objectives.

Experimental Design & Survey Development

I create the optimal choice experiment design, develop the survey instrument, and establish data collection protocols that balance statistical efficiency with respondent experience.

Data Analysis & Modeling

I apply appropriate choice modeling techniques to your data, from basic multinomial logit to advanced mixed logit models, ensuring robust preference parameter estimation.

Results & Recommendations

I deliver comprehensive analysis reports with clear preference insights, strategic recommendations, and supporting documentation for decision-making or publication.

For urgent questions, my on-demand consultation service offers quick, cost-saving solutions.

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Case Studies

I worked on large medical datasets to answer causal questions related to epidemiological determinants of disease through complex exposures. Challenges included selection bias, confounding, and missing data. I successfully developed a strategy that gave researchers confidence in their results.
I’ve worked with R&D scientists who were simultaneously running multiple experiments to answer important questions about their cutting-edge products that would have a direct impact on various stakeholders. My role was to help in designing and analyzing the experiments, balancing the conceptual purity of the Design of Experiments theory (DoE) with pragmatic concerns relating to costs and timeline. Most of this work is sealed behind a Non-Disclosure Agreement (NDA) which prevents me from elaborating more.

Don’t Just Take My Word For It…

The positive experiences of my happy collaborators showcased through their glowing testimonials, serve as powerful proof of trustworthiness and the impact of the results I deliver. These testimonials offer real-life examples of how I’ve helped research projects succeed. Here are some of their thoughts:

5/5

"He has a deep understanding of statistics, yet is able to skillfully explain complex concepts to people with little-to-no background in statistics both in French and English."

Elsa Brunet-Ratnasginham

Post-doc, UCSF

5/5

"I had never before worked with a biostatistician who speaks the same language as me! [...] Personally, our collaboration has allowed me to reconcile with statistics."

Manon Nayrac

Post-doc, CRCHUM

5/5

"I highly recommend Justin and his team for your data processing needs in order to have a more robust statistical model than the tests we are accustomed to conducting as biologists!"

Gérémy Sannier

Ph.D candidate, CRCHUM

5/5

"Thanks to him, statistics appeared to me as solutions rather than obstacles."

Mathieu Dubé

Research Associate, CRCHUM

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Justin Belair - Causal Inference Expert

My Statistics and Causal Inference Expertise

As a university-level statistics lecturer with a substantial LinkedIn following, scientists from all over the world come to me for my unique combination of academic excellence and practical experience in statistics and causal inference.

I’ve applied causal inference methods in varied settings in both academia and industry: in biomedical sciences such as nephrology, immunology, neuroscience, virology, occupational therapy, epidemiology, dermatology, psychiatry, and oncology; in natural sciences such as agronomy, ecology, and zoology; and social sciences such as communication, and psychology. The list keeps on growing!

I am currently writing an advanced textbook that I hope will give a young generation of academic and industry researches the tools needed to grapple with the complexities of causal inference, and maybe even develop a passion for the subject!

Need insights into decision-making preferences? From experimental design to advanced choice modeling, I provide the expertise to uncover the preferences that drive choices. Together, we can transform your research questions into actionable preference insights.

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Tools and Technologies

Statistical Software Excellence

Using specialized choice modeling software including R (mlogit, gmnl, apollo packages), Python (pylogit, xlogit), and dedicated DCE platforms to ensure accurate preference estimation.

Experimental Design Tools

Leveraging advanced design software including Sawtooth Software, Ngene, and R-based design packages to create statistically optimal choice experiments.

Survey Platforms

Experienced with major survey platforms including Qualtrics, Sawtooth Lighthouse, and custom survey solutions for complex choice experiment implementations.

Client Industries Served

My statistical consulting expertise extends beyond specific industries, serving clients in fields ranging from R&D in biotechnology and pharmaceuticals to researchers and Principal Investigators (PI) in academia.