Paid (Fee-Based) Events


Elaine Eisenbeisz, Owner and Principal Statistician of Omega Statistics, is available for training and workshops in statistics, clinical research, process control/quality assurance, and other topics related to statistics and good research practices. Please call or email the Omega Statistics offices to request the latest brochure and pricing for the event(s) that interests you.

Current offerings and scheduled events are listed below.

In addition to the current offerings listed below, Elaine can design an in-house training or virtual webinar to meet your specific needs. Just give her a call at 877-461-7226 or fill out the contact form on this page to leave her a message and she’ll contact you to schedule a time to discuss your needs and how she can help!

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Currently Available Offerings:

2-Day In-Person Seminars/Workshops:

• Biostatistics for the Non-Statistician
• Statistics for Process and Quality Control
• Clinical Data Management
• Fundamentals of Clinical Trial Design
• Introduction to Adaptive Design


6-Hour Virtual Webinars:

• Statistics for Process Control
• Statistics for Quality Control
• Biostatistics for the Non-Statistician


2-Hour Virtual Webinars:

• Power Analysis and Sample Size
• Multiple Imputation for Missing Data


Currently Scheduled Fee Based Events

Omega Statistics has contracted with 3rd party companies to present the following fee based events. The events are listed in chronological order. Please click on the links that interest you to learn more and to register.

Upcoming Events


2-Day Seminar: Biostatistics for the Non-Statistician

December 6th and 7th, 2018: San Francisco, CA

Learn More About the Biostatistics for the Non-Statistician Seminar

Statistics is a useful decision-making tool in the clinical research arena. When working in a field where a p-value can determine the next steps on development of a drug or procedure, it is imperative that decision makers understand the theory and application of statistics.

Many statistical softwares are now available to professionals. However, these softwares were developed for statisticians and can often be daunting to non-statisticians. How do you know if you are pressing the right key, let alone performing the best test?

This seminar provides a non-mathematical introduction to biostatistics and is designed for non-statisticians. And it will benefit professionals who must understand and work with study design and interpretation of findings in a clinical or biotechnology setting.

The focus of the seminar is to give you the information and skills necessary to understand statistical concepts and findings as applies to clinical research, and to confidently convey the information to others.

Emphasis will be placed on the actual statistical (a) concepts, (b) application, and (c) interpretation, and not on mathematical formulas or actual data analysis. A basic understanding of statistics is desired, but not necessary.

2-Hour Virtual Webinar: Power Analysis for Sample Size Calculations

December 19th, 2018

Learn More About the Power Analysis for Sample Size Webinar

The power of your study is the probability that you will find a statistically significant difference or relationship (an “effect”) if that difference or relationship (effect) truly exists in the population.

A study with too small of a sample size is under-powered. This means that even if the effect you are testing for truly exists, you won’t achieve statistical significance. You will waste time by collecting a sample that is too small to properly power a study. Why perform a research if you can’t see significance for your desired effect?

A study with too large of a sample is over-powered. This means that you’ve collected such a large sample that you will see significance even on very small effects. However, the costs of subject recruitment, data collection, and follow-up (if needed) are quite large. Recruiting more subjects than needed unnecessarily inflates the temporal and monetary costs.

In this webinar attendees will learn the statistical power analysis and techniques for determining sample size (a priori techniques) calculation. Also attendees will get to see worked examples in the free to use G*Power software. Some code and demonstrations will be provided for powering studies and performing power analysis simulations in R software.

2-Day Seminar: Clinical Data Management (CDM)

January 17th and 18th, 2019: Houston, TX

Learn More About the Clinical Data Management Seminar

Clinical data management (CDM) is paramount for a successful research. After all, Garbage In, Garbage Out (GIGO).

CDM involves all aspects of collecting, processing, and interpreting information. There are many types of computer applications and database systems to support data collection and management. However, there are elements of CDM that apply across the board.

Review and approval of drugs or devices by regulatory agencies requires the assumption that the data presented are valid and reliable. Integrity of the data is paramount to ensure confidence in the results and conclusions you will make.

This seminar is based on FDA E6 GCP Guidelines which are the basis of effective data quality management. Even if your research is not FDA regulated, the information you learn in this course will help to ensure a robust data collection and management plan.

The information conveyed in this course will also assist investigators in setting up processes for smoother data monitoring and auditing.

Examples of CRF’s and required documentation will be presented. Data collection and preparation techniques will also be demonstrated. Additionally, this workshop will provide you with the knowledge and tools needed to assure a CDM plan that holds up when the inevitable deviations from protocol occur.

DISCLAIMER: This seminar is not endorsed by, directly affiliated with, maintained, authorized, or sponsored by the Society for Clinical Data Management or any other clinical research society. All products, processes, and company names are the registered trademarks of their original owners. The use of any trade name or trademark is for identification and reference purposes only and does not imply any association with the trademark holder of their brand.

2-Hour Virtual Webinar: Tips and Techniques for Handling Missing Data

January 23rd, 2019

Learn More About the Tips for Handling Missing Data Webinar

Just removing records (listwise deletion) with missing data can reduce the power of your study and result in Type II error (when the effects are truly there, but you don’t have enough power to achieve statistical significance).

And, many of the adjustments that researchers use for handling missing data introduce bias into the data. For instance, one of the most common problems with many of the techniques is a reduction in standard error of the estimates, which results in inflated Type I errors (seeing significant findings when they do not truly exist).

Good power and low bias are hard to control to begin with. It is important to learn how to handle missing-ness to make efficient use of our data to achieve accurate and precise results. Some knowledge of linear regression is desired.

In this webinar attendees will learn the ways to deal with missing data in a data set. Some statistical reasoning on the why and when of applying various techniques in working with missing-ness in data. Attendees will also learn multiple imputation techniques using SPSS software.

6-Hour Virtual Webinar: Statistics for Process Control

January 30th, 2019

Learn More About the Statistics for Process Control Webinar

This 6-hour virtual seminar includes a presentation of the steps and techniques used to quantify variability in manufacturing processes, and to assure quality products.

The concepts and information presented will be mainly concerned with statistical process control: obtaining monitoring information (data) that is objective, unbiased, and useful for decision making. An emphasis will be placed on the set-up and use of control charts.

The objective of the seminar is to provide information that can be used immediately by personnel involved in production operations, and by supervisors and management in decision making. Although the presentation involves use of statistical techniques, presentation of statistical theory will be limited to only what is needed by the attendees to understand and implement processes and monitoring tools within the statistical framework.

Presented examples will include an emphasis on the manufacturing processes and quality assurance needs of product in the medical device and pharmaceutical industries.

Process control is constantly evolving. Therefore, historical concepts, current trends and regulatory requirements will be discussed. The presentation of statistical charts and analyses, graphical techniques for planning, trouble-shooting and problem solving will also be presented.

6-Hour Virtual Webinar: Biostatistics for the Non-Statistician

February 21st, 2019

Learn More About the Biostatistics for the Non-Statistician Webinar

Statistics is a useful decision-making tool in the clinical research arena. When working in a field where a p-value can determine the next steps on development of a drug or procedure, it is imperative that decision makers understand the theory and application of statistics.

Many statistical softwares are now available to professionals. However, these softwares were developed for statisticians and can often be daunting to non-statisticians. How do you know if you are pressing the right key, let alone performing the best test?

This webinar provides a non-mathematical introduction to biostatistics and is designed for non-statisticians. And it will benefit professionals who must understand and work with study design and interpretation of findings in a clinical or biotechnology setting.

The focus of the webinar is to give you the information and skills necessary to understand statistical concepts and findings as applies to clinical research, and to confidently convey the information to others.

Emphasis will be placed on the actual statistical (a) concepts, (b) application, and (c) interpretation, and not on mathematical formulas or actual data analysis. A basic understanding of statistics is desired, but not necessary.

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