M-Estimator
Statistical science consultancy for the life sciences that provides biostatistics, statistical programming, data science and AI/ML support for clinical development, regulatory filings, and methodological research. Services focus on design, analysis, interpretation and reporting of clinical studies (Phase 1–4), CDISC-compliant programming and submission readiness, survival/time-to-event methodology, and applied machine learning.
Industries
Nr. of Employees
small (1-50)
M-Estimator
Fort Worth, Texas, United States, North America
Services
Design, analysis, interpretation and reporting of clinical studies (Phase 1–4), development of statistical analysis plans and regulatory-defense positions.
CRF annotation, SDTM mapping, ADaM development, define-XML generation, legacy conversion and high-quality TLF production for submissions.
Implementation of non-parametric procedures to test cumulative hazard forms and proportional hazards in prespecified periods; application to oncology and other therapeutic areas.
Creation of visualizations to support interpretation of clinical and analytic results for presentations and regulatory review.
Design, analysis, interpretation and reporting of clinical studies (Phase 1–4), development of statistical analysis plans and regulatory-defense positions.
CRF annotation, SDTM mapping, ADaM development, define-XML generation, legacy conversion and high-quality TLF production for submissions.
Implementation of non-parametric procedures to test cumulative hazard forms and proportional hazards in prespecified periods; application to oncology and other therapeutic areas.
Creation of visualizations to support interpretation of clinical and analytic results for presentations and regulatory review.
Expertise Areas
- Biostatistics for clinical development
- Survival analysis and time-to-event methodology
- CDISC-compliant statistical programming
- Clinical study design and statistical consulting
Key Technologies
- Kaplan–Meier estimation and survival analysis
- Non-parametric hypothesis testing for hazard functions
- Proportional hazards testing
- Simulation-based power and operating-characteristics evaluation
News & Updates
Participation and session highlights from a regional biotechnology and life sciences summit in Dallas, TX.
Reference to a podcast episode featuring scientific interviews relevant to natural science and clinical research.
Peer-reviewed methodological paper describing flexible non-parametric testing procedures for cumulative hazard functions and proportional hazards testing applied to oncology.
Support or coverage of a training program that prepared graduates as statistical programmers (reported coverage and external news links).
Participation and session highlights from a regional biotechnology and life sciences summit in Dallas, TX.
Reference to a podcast episode featuring scientific interviews relevant to natural science and clinical research.
Peer-reviewed methodological paper describing flexible non-parametric testing procedures for cumulative hazard functions and proportional hazards testing applied to oncology.
Support or coverage of a training program that prepared graduates as statistical programmers (reported coverage and external news links).