Our Statistical Consulting Team’s Expertise
Statistical Consulting
Our clients cite the following reasons for choosing to work with AMSTAT Consulting:
- Our principals have PhDs in statistics from leading universities, such as Harvard, Stanford, and Columbia. In addition, they include nationally renowned scholars who are also talented professors. Thus, they have extensive backgrounds in statistics and biostatistics.
- Our statisticians have an average of 25 years of technical experience. Additionally, they are experts in statistical analysis, such as t-test, ANOVA, ANCOVA, traditional regression, logistic regression, MANOVA, MANCOVA, factor analysis, cluster analysis, survival analysis, time series analysis, correlation analysis, meta-analysis, and more advanced statistical techniques such as structural equation modeling (SEM), hierarchical linear modeling (HLM), and path analysis.
- Our statisticians use various software packages, including SPSS, SAS, Stata, HLM, Mplus, R, SPSS Amos, SPSS Modeler, Azure, JMP, Python, WinBUGS, Minitab, SYSTAT, LISREL, EQS, Smart PLS, WarpPLS, EViews, and many others.
- Our statistical consultants use the latest statistical software available in the market today. In addition, they can apply the required technical and specialized techniques and procedures of statistics. Thus, we are confident that you will be satisfied with our statistical consultants.
- We are more reasonably priced than most other statistical consulting firms. Thus, our fees pale in comparison to the savings our work generates for our clients.
- We offer friendly support and ultra-fast turnaround times. Therefore, over 90% of clients request our assistance more than once, as they are almost universally happy with the different statistical consulting brands we offer.
- We possess good communication skills. Thus, we can interact with our clients fluently and comfortably.
- We are members in good standing of the Statistical Consulting section of the American Statistical Association.
Our Services
We are happy to provide the statistical consulting 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, coding, merging, managing, and cleaning the data
- Determining the ideal sample size
- Conducting analyses and assessing assumptions to examine the research questions
- 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 the results, including tables and figures
- Providing syntax and raw output file
- Explaining and interpreting 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
- Supporting you until your project is complete.
Data Management
We are dedicated to detecting and correcting corrupt or inaccurate records from a record set, table, or database. The process of data cleaning includes data auditing, workflow specification, workflow execution, post-processing, and controlling. We can use popular methods. These 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 for a case. We run outlier analyses such as a run-sequence plot, a scatter plot, a histogram, and a box plot.
Data Analysis
Our statistical consultants specify specific statistics to address the research questions. We are experts in statistical analysis, including but not limited to the following:
- linear, logistic, and hierarchical regression analysis
- correlation analysis
- chi-square testing
- t‑tests, ANOVA, MANOVA, ANCOVA, MANCOVA
- structural equation modeling (SEM), multilevel SEM, confirmatory factor analysis (CFA), multilevel CFA
- factor analysis, principal component 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 models
- linear mixed models
- distribution analysis
- predictive analytics
- ensemble analysis
- de-identification
- trend analysis
- sensitivity analysis
- negative binomial regression
- interim analysis
- decision trees
- item analysis
- nonparametric tests
- statistical and decision modeling
- MaxDiff
- segmentation and cluster analysis
- conjoint/discrete choice
- propensity score analysis
We use various software packages, including but not limited to the following:
- SPSS
- SAS
- Stata
- HLM
- Mplus
- R
- SPSS Amos
- SPSS Modeler
- Azure
- JMP
- Python
- WinBUGS
- Minitab
- SYSTAT
- LISREL
- EQS
- Smart PLS
- WarpPLS
- EViews
Validity and Reliability
We ensure that the results are reliable and valid. For example, we can test reliability (e.g., Cronbach’s alpha, test-retest reliability, split-half reliability, inter-rater reliability) and validity (e.g., content validity, construct validity, criterion validity).
Examples of Our Statistical Consulting Projects
Internet Use
Our statistical consultants measured the impact of internet use on perceived performance. We performed a regression analysis to determine that internet use significantly affected perceived performance (β = 0.82, p < 0.05). [...]
Relative Risk of Lung Cancer
We compared the difference in relative risk (RR) of lung cancer between the intervention and control groups. The intervention group exhibited an increase in RR of lung cancer from pre to post (p < 0.05). [...]
Blood Pressure
A global hospital hired our statistical consultants to compare the difference in blood pressure between patients with cancer and patients without cancer. Thus, we found a significant difference in blood pressure between patients with [...]
Financial Performance
We measured the impact of banking fees on financial performance. Banking fees significantly and positively affected financial performance (β = 0.46, p < 0.05). We performed a regression analysis by using SPSS. [...]
This list shows a sample of the past clients.
Client Success Stories
EndoLogic requested statistical consulting to measure the impact of its medical device. Our research led to the appropriate solution by examining the effect of its medical device.
Dr. Zamir S. Brelvi, CEO of EndoLogic, says, “We have been very pleased with working with AMSTAT Consulting. The service was custom-tailored and completed on time. 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.”
Endo LogicPrisma Health hired our statistical consultants. Therefore, we analyzed the impact of demographic characteristics on referrals.
Dr. Haritha Boppana, a physician at Prisma Health, says, “I needed 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.”
Prisma HealthPhoenix Children’s Hospital asked us to analyze patients managed on the pain service. Therefore, our statistical consultants measured the effect of the pain service.
Dr. Raj Singhal, research director of pain management at Phoenix Children’s Hospital, says, “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 Consulting for all of our future needs, and I am thrilled to have been introduced to them.”
Phoenix Children’s HospitalUNICEF requested statistical consulting. Thus, we analyzed the impact of positive peer network injunctive on immunization use.
Dr. Ibrahim Mohammed, a health specialist at UNICEF, says, “AMSTAT Consulting 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 every one of my demands. AMSTAT Consulting is highly recommended!”
UNICEFMount Royal University hired our statistical consultants. Thus, we analyzed the impact of navigation ease in e-learning course websites on student learning.
Dr. Vincent Salyers, former dean of Mount Royal University (current dean of Gonzaga University), says, “I have worked closely with AMSTAT on the data analysis/results of two research projects, so feel as though I am knowledgeable about their expertise. The company provided me with reliable statistical analysis and results to translate into a publishable format on all accounts. They are conscientious experts who provide keen insights into appropriate statistical analysis give various data sets. I highly recommend them for your statistical support needs.”
Mount Royal UniversityDiscover Our PhD-level Experts’ Secret Tutorials
Independent Samples T-Test
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 [...]
Binomial Logistic Regression
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 [...]
Paired-Samples T-Test
The paired-samples t-test is used to determine whether the mean difference between paired observations is statistically significantly different from zero. The participants are either the same individuals tested at two time points or under [...]
Regression Analysis
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: [...]
