AMSTAT Consulting is a specialist biometrics CRO offering statistical consulting, clinical trial reporting, data management, and data science services by providing expert consultants and managing and delivering in-house projects, FSP-style arrangements, and preferred partnerships.
All of our principals have PhDs in statistics at leading universities, including Harvard, Stanford, and Columbia. They include nationally renowned experts.
They have extensive backgrounds in biostatistics. They 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).
Our programmers have 3,700 years of accumulated programming experience across the company. They are experts in statistical programming languages such as SPSS, SAS, Stata, R, HLM, Mplus, SPSS Amos, SPSS Modeler, Azure, JMP, WinBUGS, Minitab, Match!3, and Access.
Our number one priority is ensuring on time, quality work: every project undertaken is supervised on methodology and utilizes internal processes designed to guarantee optimal quality, inspired by 3,700 years of accumulated programming experience across the company.
Over 90% of our clients request our assistance more than once, as our clients are almost universally happy with our different brands of consulting.
We offer personalized, comprehensive, and friendly support during and after your consultation with us.
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 [...]
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 [...]
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 [...]
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: [...]
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 [...]
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 [...]
We want to hear about the specifics of your project. One of our experts will provide personalized recommendations and ideas. We will take the time to learn about your project and discuss how to help you.
This is a $200 consultation we are providing for free. What is there to lose?