Driving Intelligent Decisions For Healthcare Through Data, AI, and Advanced Research Analytics

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Nalyxe Nalyxe

Biostatistics Clinic for Complex Studies

Expert biostatistical design and analysis for clinical trials, cohorts, survival/time-to-event, longitudinal data, and high-stakes reporting using SPSS, Python, R, SAS, GraphPad, Jamovi, Stata

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Research Challenges

Complex Studies Require Statistical Precision

Designing and analyzing clinical or observational studies often involves complex endpoints, strict regulatory expectations, and methodological challenges that cannot be solved with standard analysis alone.
 Unclear statistical planning or poorly aligned analysis can delay studies, weaken conclusions, and impact publication outcomes.

Our biostatistics clinic helps research teams build statistically sound studies and deliver results that stand up to scientific and regulatory review.

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Our Biostatistics Analysis Services Are Not Limited To

Development of Statistical Analysis Plan (SAP)
Full SAP drafting, SAP-to-protocol consistency checks,
Mock shells for TLFs, QC review of SAP,
Traceability matrix
Survival & Time-to-Event Analytics
Kaplan–Meier curves fitting, Cox proportional hazards models, Competing risks analysis, Parametric survival models (Weibull/log-normal), Handling censoring and left truncation, Computing the life tables
Sample size & Power Computation
Superiority/non-inferiority/equivalence sample size, Cluster randomized and stepped-wedge designs, Survival and event-driven sample size, Repeated measures and MMRM-based power, Adaptive sample size re-estimation
Trial Design & Statistical Strategy
Protocol review and endpoint, Sample size & power calculations, Randomization and stratification schedules, Interim analysis strategy, and DSMB-ready outputs
Longitudinal & Repeated Measures
MMRM and mixed models (LMM/GLMM), GEE for correlated outcomes, Covariance structure selection and model fit reporting, and Missing longitudinal data strategies
Reproducible Code Research
Clean, commented scripts (R/Stata/SAS),
Versioning and audit trail documentation,
End-to-end reproducibility packaging
Epidemiological Data Analytics
Incidence and prevalence estimation Risk factor analysis & adjusted associations Cluster analytics, Population attributable fraction & burden estimation, Screening program analytics, Spatial and temporal trend analysis,
Health Economics & Cost-Effectiveness Analytics
Cost identification and costing framework, Utility mapping and QALY estimation, Decision trees and Markov models, ICER computation and dominance assessment, Probabilistic sensitivity analysis (PSA)
How We Work

A Structured Statistical Path from Study Design to Validated Results

Complex clinical and research studies require more than statistical calculations they require a structured methodology that ensures scientific accuracy, regulatory alignment, and reproducible outcomes.
 Our biostatistics workflow guides every project from protocol understanding to validated reporting, helping research teams move forward with confidence.

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04 Steps Process
01
Understand Study Objectives
We review protocols, endpoints, and research goals to align statistical strategy with scientific intent.
02
Statistical Planning & Modeling
Development of SAP, sample size calculations, and modeling frameworks tailored to study design.
03
Analysis & Validation
Execution of validated statistical models with quality checks, subgroup evaluation, and methodological verification.
04
Reporting & Delivery
Clear, publication-ready outputs supported by reproducible code and transparent documentation.
Our Biostatistics Consulting Advantage

Why Organizations Choose Nalyxe for Biostatistical Expertise

Nalyxe delivers accurate, transparent biostatistics for reliable, publication-ready results.

Clinical & Research Domain Expertise

Confidential & NDA-Ready Collaboration

Transparent & Reproducible Methodology

End-to-End Statistical Support

Long-Term Research Partnership

Statistical Platforms & Tools

We use industry-standard tools to ensure accurate, reliable, and reproducible biostatistical results.

FAQs

Clarity for Your Statistical & Research Decisions

Researchers often ask about methods and regulations answered by our biostatistics experts

What is a Biostatistics Data Analysis Clinic, and how does it work?

It’s a structured, expert-led workflow where we diagnose your study needs, choose defensible methods, run validated analyses, and deliver decision-ready outputs with clear documentation and handover.

Can you develop or review a Statistical Analysis Plan (SAP)?

Yes, we create or review SAPs to align endpoints, populations, models, covariates, and reporting with your protocol and objectives.

Do you support survival analysis and time-to-event outcomes?

Yes, Kaplan–Meier, Cox models, parametric survival, and time-to-event reporting with transparent assumptions.

Can you handle competing risks or recurrent events data?

Yes, appropriate competing-risk and recurrent-event methods with interpretation guidance and sensitivity checks.

Do you perform mixed effects models (GLMM) and multilevel analysis?

Yes, multilevel/hierarchical models for clustered or nested data, with clear reporting of fixed and random effects.

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