AMSTAT’s Expertise

AMSTAT has become nationally recognized for providing its biostatistical consulting services to numerous pharmaceutical and medical device companies. Our successful clients cite these reasons for choosing to work with AMSTAT.

All of our principals have PhDs 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 and qualitative 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. They are experts in using qualitative data analysis software such as NVivo, Nud*ist, HyperResearch, and Atlas.

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. 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 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, NVivo, WinBUGS, Minitab, Match!3, and Access.

Impact Stories

Redefining strategy

Doubled valuation and reignited 40 percent year-on-year growth for a pharmaceutical company through a 2-year partnership to analyze their product and strategy to unlock new customers and partners.

Radical transformation

Doubled the share price of a large, global pharmaceutical company by using statistical analysis.

Boosting annual revenue growth

Reignited growth for a global pharmaceutical company by using statistical analysis to understand and rapidly optimize marketing activities and customer journeys, taking stagnant revenue growth to 13 percent over the course of 16 months.

Growing direct-to-consumer businesses

Helped both established and upstart pharmaceutical companies in geographies around the world add millions of customers by using statistical analysis.

100+ pharmaceutical companies served

100+ pharmaceutical companies served

100+ medical device companies served

100+ medical device companies served

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 [...]

See our PhD-level experts’ secret tutorials

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