AMSTAT’s Expertise

AMSTAT has become nationally recognized for providing data management and biostatistical analysis. Our successful clients cite these reasons for choosing to work with AMSTAT.

All of our principals have PhDs in statistics at leading universities, including Harvard, Stanford, and Columbia. They include nationally renowned scholars. They have extensive backgrounds in biostatistics and over 100 years of practical experience in quantitative methods. 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, predictive modeling, cluster 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, and advanced statistical analysis). 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 fees usually pale in comparison to the savings and additional profits that our work produces for our clients. 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 are more reasonably priced than most other consultants offering biostatistical consulting. We offer personalized, comprehensive, and friendly support during and after your consultation with us. We offer ultra-fast turnaround times. We are members in good standing of the Statistical Consulting section of the American Statistical Association.

Our Services

We are happy to provide the help you need at any or all of the following steps in earning the data-based answers you request.

Establishing and operationalizing your hypotheses and research questions

Providing ample instruction on the methods used

Inputting, organizing, and cleaning the data

Implementing the statistical analyses

Testing reliability (such as Cronbach’s alpha, test-retest reliability, split-half reliability, and inter-rater reliability) and validity (such as content validity, construct validity, criterion validity, internal validity, and external validity)

Writing up all results, including APA tables and figures

Providing syntax and raw output file

Explaining the results

Allowing unlimited e-mail and phone support to ensure that you completely understand the results of the analysis

Conducting two rounds of incidental statistics (i.e., if you would like additional statistics)

Preparing an effective PowerPoint Presentation.

Data Management and Test Results for Reliability and Validity

AMSTAT is dedicated to detecting and correcting corrupt or inaccurate records from a recordset, table, or database. The process of data cleaning includes data auditing, workflow specification, workflow execution, post-processing, and controlling. We can use popular methods. Those include parsing, data transformation, duplicate elimination, and statistical methods.

By analyzing the data using the values of mean, standard deviation, range, and clustering algorithms, we can find values that are unexpected and thus erroneous. We can examine any standardized residual greater than about 3 in absolute value, Hat element greater than 3p/n (p=k+1, k degrees of freedom), a Cook’s distance > 1, and Mahalanobis’s distance. We can run outlier analysis such as a run-sequence plot, a scatter plot, a histogram, and a box plot.

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

Statistical Analysis

We can design and perform the required statistical analyses.  Here is a sample of some of the analytical tools with which we are familiar:

  • Correlation Analysis, T-test, Chi-square Test, Regression Analysis, Logistic Regression, Hierarchical Regression Analysis, Factor Analysis, Principal Components Analysis, One-way ANOVA/ANCOVA, One-way MANOVA/MANCOVA, Factorial ANOVA/ANCOVA, Repeated Measures ANOVA/ANCOVA, Repeated Measures MANOVA/MANCOVA, Nonparametric Test (Wilcoxon signed rank test, Friedman test, Kruskal-Wallis test, Mann-Whitney test, Spearman Rank Correlation), Structural Equation Modeling (SEM), Multilevel SEM, Confirmatory Factor Analysis (CFA), Multilevel CFA, Exploratory Factor Analysis, Mediation Analysis, Moderation Analysis, Time Series Analysis, Spatial Time-series Modeling, Cluster Analysis, Cox Regression, Kaplan-Meier Survival Analysis, Trend Analysis, Sensitivity Analysis, Hierarchical Linear Modeling (HLM), Bayesian Analysis, Bayesian Cox Regression, Joint Hierarchical Bayesian Modeling, Latent Class Analysis, Longitudinal Growth Modeling, Mixed-Effects Regression Model, Meta-Analysis, Mixture Model, Linear Mixed Models, Predictive Modeling, Distribution Analysis (e.g., Lognormal, Weibull, Gamma), Decision Tree, Ensemble Analysis, De-identification, Interim Analysis, Item Analysis, Discriminant Analysis, Binomial Test, Heterogeneity Test, Multidimensional Scaling, Tau-U Analysis, Negative Binomial Regression, and Advanced Statistical Analysis

We have expertise in virtually every statistical and qualitative software package, including but not limited to:

  • SPSS, SAS, Stata, HLM, Mplus, R, SPSS Amos, SPSS Modeler, Azure, JMP, WinBUGS, Minitab, Match!3, Access, NVivo, Nud*ist, HyperResearch, and Atlas.

This list shows a sample of the past clients.

Examples of our work

Relative Risk of Lung Cancer 

September 14th, 2020|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

September 13th, 2020|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

September 12th, 2020|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

September 11th, 2020|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 [...]

Explore more studies

Discover our PhD-level experts’ secret tutorials

Secret Tutorial: Linear Regression Analysis

September 14th, 2020|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

September 13th, 2020|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

September 11th, 2020|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

September 10th, 2020|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 [...]

Learn more

Featured Client Success Stories

Phoenix Children’s Hospital

“They have been instrumental in helping with our statistical needs. In addition to their professionalism, they have been prompt and thorough with all of our requests. Their work is impeccable, and I would recommend their services to anyone in need of assistance with methods or interpretation. We plan on using AMSTAT for all of our future needs, and I am thrilled to have been introduced to them.” – Dr. Raj Singhal, MD, Research Director of Pain Management, Phoenix Children’s Hospital

Prisma Health Greenville Memorial Hospital

“I am a physician and was in need of statistical analysis of research data. They called me and explained the process involved in data analysis. They were always very prompt, helpful, intelligent, and took time explaining the various tests used in conducting data analysis. Thank you so much!! I look forward to working with you in the future.” – Dr. Haritha Boppana, MD, Prisma Health Greenville Memorial Hospital


“AMSTAT is a perfect example of poise, understanding, and patience. They diligently follow up and never lose their calm. I had a hundred questions and countless demands, and they took their time to listen and implement each and every one of my demands. AMSTAT is highly recommended!” – Dr. Ibrahim Mohammed, MD, UNICEF


“We have been very pleased with working with AMSTAT. The service was custom-tailored and on-time completion. The statistical report was detailed with excellent tables. The cost of the services was affordable for a start-up company such as EndoLogic! They are very detail-oriented and like to know the project thoroughly that is being analyzed.” – Dr. Zamir S. Brelvi, MD, PhD, CEO, EndoLogic

Gonzaga University

“I have worked closely with AMSTAT on the data analysis/results of two research projects. Thus, I am knowledgeable about their expertise. On all accounts, the company provided me with reliable statistical analysis and results. They are conscientious experts who provide keen insights into appropriate data analysis given various data sets. I highly recommend them for your data needs!” -Dr. Vincent Salyers, EdD, Dean and Professor, School of Nursing and Human Physiology, Gonzaga University

Mount Royal University

“Extremely professional. Attends to your project needs with skills and expertise. Pays attention to all details. Offers suggestions and recommendations for better and more effective use of your data. Creative and sincere. Thank you very much.”- Prof. Mohamed Toufic El Hussein RN, PhD
Associate Professor, School of Nursing, Mount Royal University

See our 5-star reviews

Call us now at (301) 800-0038

Contact us now