KnowTechInfo’s experienced Biostatistics team has consistently delivered high quality statistical services for each and every study we have supported. We have extensive experience with studies across all phases of the pre-and post-development life-cycle (Phase I, II, III, post-marketing studies, market access clinical effectiveness studies, proof of concept, and epidemiology studies). Each study will be led by an experienced Biostatistician who will work with the project teams to deliver high quality results. At KnowTechInfo, we tailor the biostatistical services required for the study and can provide any or all of the following services:

Protocol Development

  • Optimal study design selection to achieve the goals of the protocol
  • Research and selection of appropriate statistical analysis methods
  • Sample size calculations, including simulations when required, for optimal study design
  • Protocol writing in collaboration with the clinical team

Randomization Schedules

  • Traditional and dynamic allocation schemas
  • Complex stratified allocations
  • Material lists and kit allocations

Statistical Analysis Plans

  • Detailed statistical analysis plans that are ICH E9 compliant
  • Table, Listing, and Figure Shell delivered with the SAP

Integrated summaries of safety (ISS) and efficacy (ISE)

Quantitative pharmacoepidemiology design and analysis, including patient registries

Statistical report writing

Statistical analysis and support for interim analyses and Data Monitoring Committee (DMC)

  • Blinded and unblinded support, with appropriate firewalls to preserve trial integrity
  • Full DMC support to include statistician representation, charter preparation, and DMC analyses

Preparation of case report tabulations (CRTs)

Data mining and exploratory analyses


KnowTechInfo Biostatisticians offer additional expertise in the statistical sciences not often found in other service providers. In addition to standard statistical analysis methods applied to clinical research we are skilled in the following areas:

Mixed-effects models including mixed-effects models for repeated measures (MMRM)

Pattern mixture and selection models assessment of missing data mechanisms (MCAR, MAR, MNAR)

Complex descriptive, exploratory and correlation modeling (factor analysis, path analysis)

Simulation (Monte Carlo, boot strap, randomization tests)

Industrial statistics (control charts, variance component modeling)

Questionnaire development and validation (item analysis, reliability and validity coefficients across many different instruments)

Survey research design and analysis (including complex survey designs and patient surveys and registries)

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