OUR STATISTICAL & RESEARCH SERVICES

Your statistical partner
for researchers, CROs & institutions.

From a single thesis to a full clinical program — rigorous biostatistics for academic researchers, CROs & pharma, and universities & institutions.

For academic researchers & postgraduate students — from a first thesis to a documented analysis.

Sample Size Calculation

01

Determine the exact number of participants your study needs to detect meaningful effects with statistical confidence. Avoid wasted resources and underpowered results.

  • Power analysis for RCTs, cross-sectional, case-control, and cohort designs
  • Sample size estimation for hypothesis tests, confidence intervals, and equivalence/non-inferiority
  • Attrition adjustments, clustered designs, and multiple comparison corrections
  • Software: G*Power, nQuery, PASS, R (pwr, WebPower, simr)
Get StartedFree Assessment

Survey Analysis

02

Turn raw questionnaire responses into validated, publishable insights. From instrument design to complex psychometric modelling — we handle every layer.

  • Questionnaire design consultation, cognitive testing, and pilot analysis
  • Reliability analysis: Cronbach's alpha, McDonald's omega, test-retest, ICC
  • Exploratory (EFA) & Confirmatory (CFA) Factor Analysis
  • Structural Equation Modeling (SEM), path analysis, and measurement invariance
Get StartedFree Assessment

Clinical Biostatistics

03

End-to-end statistical support for clinical and health research — from raw data to publication-ready outputs, fully compliant with international standards.

  • Comprehensive descriptive & inferential analysis for all data types
  • Parametric and non-parametric hypothesis testing tailored to study design
  • Regression modelling: linear, logistic, Poisson, ordinal, and multinomial
  • Model diagnostics, assumption checking, outlier detection, and sensitivity analysis
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Statistical Modeling

04

Uncover hidden patterns in your data with advanced regression, machine learning, and longitudinal models. Built for complex research questions.

  • Mixed-effects models (LMM, GLMM) for longitudinal & clustered data
  • Survival analysis: Kaplan-Meier, Cox regression, competing risks, parametric models
  • Generalized Estimating Equations (GEE) for repeated measures
  • Machine learning for research: random forests, gradient boosting, SVM with interpretability
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Bioinformatics

05

Extract meaningful biological insights from high-throughput genomic data using state-of-the-art pipelines and rigorous statistical methods.

  • Single-cell RNA-seq analysis: QC, normalisation, integration, clustering, annotation
  • Bulk RNA-seq, ChIP-seq, and ATAC-seq processing pipelines
  • Differential expression, gene set enrichment, and pathway over-representation analysis
  • Multi-omics integration (transcriptomics, proteomics, metabolomics)
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Meta-Analysis

06

Synthesise evidence across multiple studies with rigorous methodology. We handle everything from literature screening to publication bias assessment.

  • Systematic search strategy development and study selection support
  • Effect size extraction and transformation (OR, RR, SMD, Hedges' g, correlation)
  • Fixed-effects, random-effects (DL, REML), and hierarchical Bayesian models
  • Heterogeneity analysis, meta-regression, subgroup analysis, and publication bias diagnostics
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Data Visualization

07

Present your findings with publication-ready figures, charts, and diagrams that communicate complex results clearly and professionally.

  • Publication figures in R (ggplot2), Python (matplotlib/seaborn), and GraphPad Prism
  • Custom colour palettes, typography, and layouts matching journal guidelines
  • Multi-panel figures with shared legends, highlighting, and annotations
  • Forest plots, Kaplan-Meier curves, volcano plots, heatmaps, and correlation matrices
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Data Cleaning & Validation

08

Start every analysis with data you can trust. We audit, clean, and validate your datasets so your results are defensible from the ground up.

  • Raw data auditing: missingness patterns, duplicate detection, logic checks
  • Missing data handling with multiple imputation (MICE, Amelia) and sensitivity analysis
  • Outlier identification using statistical and visual diagnostics
  • Data standardisation, variable coding, transformation, and full cleaning documentation
Get StartedFree Assessment
RESEARCHERS FROM

Researchers from universities and institutions

King Saud University
King Saud University
King's College London
King's College London
Ain Shams University
Ain Shams University
Princess Nourah University
Princess Nourah University
Umm Al-Qura University
Umm Al-Qura University
American University in Cairo
American University in Cairo
Al Faisal University
Al Faisal University
German University in Cairo
German University in Cairo
University of Birmingham Dubai
University of Birmingham Dubai
University of Nottingham
University of Nottingham
University of Queensland
University of Queensland
King Saud University
King Saud University
King's College London
King's College London
Ain Shams University
Ain Shams University
Princess Nourah University
Princess Nourah University
Umm Al-Qura University
Umm Al-Qura University
American University in Cairo
American University in Cairo
Al Faisal University
Al Faisal University
German University in Cairo
German University in Cairo
University of Birmingham Dubai
University of Birmingham Dubai
University of Nottingham
University of Nottingham
University of Queensland
University of Queensland
King Saud University
King Saud University
King's College London
King's College London
Ain Shams University
Ain Shams University
Princess Nourah University
Princess Nourah University
Umm Al-Qura University
Umm Al-Qura University
American University in Cairo
American University in Cairo
Al Faisal University
Al Faisal University
German University in Cairo
German University in Cairo
University of Birmingham Dubai
University of Birmingham Dubai
University of Nottingham
University of Nottingham
University of Queensland
University of Queensland

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