Our Expertise

We have become nationally recognized for providing statistical analysis. Our successful clients cite these reasons for choosing to work with us.

  • All of our principals have PhDs in statistics at leading universities, including Harvard, Stanford, and Columbia. They include nationally renowned experts.
  • Our programmers have 3,700 years of accumulated programming experience across the company.
  • They have seen the changes in the industry and work to implement all of the latest advances in data standards, technology, and industry requirements to create efficiencies in your trial data. Our programmers can offer our clients clean and precise clinical data throughout your program.
  • We can support the planning, design, and analysis of your clinical trial program. Regardless of the complexity of your project, we can provide expert statistical solutions and experienced technical advice.
  • We provide a variety of services to understand the effect of a test product on safety, efficacy, or other points of interest.
  • We carry out planned analyses which include creation and QC of analysis datasets and tables, listings, and figures.
  • Our team ensures accurate results in a timely fashion. Quality control is achieved for analysis datasets, tables, listings, and figures via independent programming according to dataset specifications or the SAP.
  • We provide many ad hoc analyses for publication summaries and external/internal review meetings.

Our Services

  • Statistical input into study design and protocol development
  • Adaptive study designs
  • Sample size calculations
  • Analysis plans
  • Optimizing study success
  • Identifying the primary endpoint
  • Modeling and simulation
  • Prediction of drug exposure
  • Optimal evaluation of information for on-going clinical trials (interim analyses, sequential trial monitoring)
  • Independent data monitoring committees
  • Setting up randomization schemes
  • Multiplicity (optimally evaluate more than one outcome in a trial)
  • Regulatory advice
  • Observational and epidemiological studies
  • Interpretation of results
  • Data visualization
  • Statistical training
  • CDISC and ADaM Submission-ready Dataset Development and Quality Control for Submission Compliance
  • Analysis of Dataset Development and Quality Control
  • Analysis of Dataset Development and Quality Control for Integrated Summaries of Safety (ISS) and Integrated Summaries of Efficacy (ISE))
  • Tables, Listings, and Figures Development and Quality Control
  • Tables, Listings, and Figures Development and Quality Control for ISS and ISE
  • Interim Analysis Support
  • Annual Clinical Trial Safety Updates
  • Data Monitoring Committee,  Safety Committee, and Endpoint Committee Support

Statistical Analysis

We are experts in statistical analysis (e.g., linear regression, logistic regression, hierarchical regression analysis, correlation analysis, chi-square test, t-test, ANOVA, MANOVA, structural equation modeling (SEM), multilevel SEM, confirmatory factor analysis (CFA), multilevel CFA, factor analysis, principal components analysis, time series analysis, Cox regression, Kaplan-Meier survival analysis, hierarchical linear modeling (HLM), meta-analysis, Bayesian analysis, latent class analysis, longitudinal growth modeling, mixture model, linear mixed models, distribution analysis, ensemble analysis, de-identification, trend analysis, sensitivity analysis, negative binomial regression, interim analysis, decision tree, item analysis, nonparametric test, statistical and decision modeling, maxDiff, segmentation and cluster analysis, conjoint/discrete choice, predictive analytics).

Test Results for Reliability and Validity

We can test reliability (such as Cronbach’s alpha, test-retest reliability, split-half reliability, and inter-rater reliability). In addition, we can test validity (such as content validity, construct validity, criterion validity, internal validity, and external validity).

Examples of Our Work

Relative Risk of Lung Cancer 

January 15th, 2021|2 Comments

We compared the difference in relative risk (RR) of lung cancer between the intervention and control groups. The hypothesis was as follows: H1: The intervention group will have an increase in relative risk (RR) of [...]

Blood Pressure

January 14th, 2021|0 Comments

We examined the difference in blood pressure between patients with cancer and patients without cancer. The hypothesis was as follows: H1. There is a significant difference in blood pressure between patients with cancer and [...]

Bending Stiffness

January 13th, 2021|0 Comments

We measured the difference among the 2.0mm RP and 2.0mm SP in bending stiffness, bending strength, and bending structural stiffness. The hypothesis was as follows: H1: There is a significant difference among the 2.0mm RP [...]

Compound D-600

January 13th, 2021|0 Comments

We examined the effect of compound D-600 (methoxyverapamil) on gluconeogenesis. The hypothesis was as follows: H1: There is a significant effect of compound D-600 on gluconeogenesis. A regression analysis was conducted. There was a [...]

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Discover our experts’ secret tutorials

Secret Tutorial: Linear Regression Analysis

January 15th, 2021|0 Comments

A simple linear regression assesses the linear relationship between two continuous variables to predict the value of a dependent variable based on the value of an independent variable. More specifically, it will let you: [...]

Secret Tutorial: Independent Samples T-Test

January 14th, 2021|0 Comments

The independent-samples t-test is used to determine if a difference exists between the means of two independent groups on a continuous dependent variable. More specifically, it will let you determine whether the difference between [...]

Secret Tutorial: Binomial Logistic Regression

January 13th, 2021|0 Comments

A binomial logistic regression attempts to predict the probability that an observation falls into one of two categories of a dichotomous dependent variable based on one or more independent variables that can be either [...]

Secret Tutorial: One-Way ANOVA

January 12th, 2021|0 Comments

If you want to determine whether there are any statistically significant differences between the means of two or more independent groups, you can use a one-way analysis of variance (ANOVA). For example, you could [...]

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