Causality in Statistical Power: Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size
My newest published article in Scientifica is now available for download online and on the Research Engineer website. The creation of the Statistical Power engine of Research Engineer led me to write the article. Click on the Download Article button below to download a .pdf directly from the website or click on the Statistical Power button to be taken to the aforementioned engine. Many thanks and regards to everyone that uses Research Engineer! -EH
Curriculum vitae for Eric Heidel, Ph.D.
Academic and work history for the Owner and Operator of Scale, LLC and Research Engineer
In an effort to further promote the efficacy and effectiveness of Research Engineer, I am publishing the most current version of my curriculum vitae. I greatly appreciate everyone using the website and I want them to know that I'm the real deal. I maintain, promote, and publish all of the original content in Research Engineer. Creating a website (and business) has been one of the greatest experiences of my life and the rewards for my efforts are starting to come to fruition.
However, I also have the distinct privilege of being a member of the faculty at the University of Tennessee Graduate School of Medicine (UTGSM). Dr. James Neutens, Dr. William Metheny, Dr. Eddie Moore, and Dr. Mitchell Goldman gave me the opportunity of a lifetime when they hired me out of obscurity as a 1st year graduate student in Counselor Education at the University of Tennessee, Knoxville. They entrusted me with the research endeavors of medical residents, fellows, faculty, and staff at the UTGSM and allowed me to learn the art of research design and statistical consultation in a great work environment. Then, they honored me with a newly created appointment as a junior faculty member at the UTGSM, where I have worked since June, 2012.
I also want to give "props" to my Mom and Dad. They opened every door for me in life and believed in me, even when they should not have, and even when I did not believe in myself. We will get our trophy back one day, I promise.
And to my wife and step-kids, who have supported me since the inception of Scalë, LLC and Research Engineer, I pledge my love, my time, and my life. I will be the one in one hundred.
Click on the button below to review my curriculum vitae. And please realize that it would not look like it does without the aforementioned people and institutions above taking a chance on me. I am humbled and honored to be in this position and will continue to fight the good fight in my position as a faculty member at UTGSM, Owner and Operator of Scalë, LLC and Research Engineer, and as a man.
R. Eric Heidel, Ph.D.
SPSS has a user-friendly interface and powerful capabilities
Conducting statistics and interpreting outputs is easy in SPSS
Statistical Package for the Social Sciences (SPSS; Armonk, NY, IBM Corp.) is a statistical software application that allows for researchers to enter and manipulate data and conduct various statistical analyses. Step by step methods for conducting and interpreting over 60 statistical tests are available in Research Engineer. Videos will be coming soon. Click on a link below to gain access to the methods for conducting and interpreting the statistical analysis in SPSS.
Research Engineer is designed to get you to the correct research question, research design, sample size, database, and statistical test
Based on your decisions to the questions presented, you will get to right place
A few words on what I'm doing on here. I am a biostatistician, methodologist, psychometrician, and counselor. Everyday, the incredibly intelligent people I work with including physicians, residents, fellows, staff, and faculty feel anxiety when it comes to statistics and research. Research has shown that statistics can induce cognitive dissonance in an individual due to limited experiences and competencies. The collective unconscious has sequestered statistics and research into a dark corner and that's scary.
Research and statistics are the methods by which we, as scientists, analyze, synthesize, and evaluate our research findings in a manner that can be generalized to the appropriate audience. If our methods for communicating research findings causes cognitive dissonance, just because it relates to research and statistics, then how can one ever really be able to generalize the clinical literature and integrate it into clinical practice?
After seven years of being the one to induce cognitive dissonance in others related to research and statistics, I decided to make a useful tool for students and researchers that could alleviate some of the feelings of anxiety associated with research and statistics. I built Research Engineer.
Research Engineer is designed to get you to the correct research question, research design, sample size, database, statistical test, evidence-based medicine intervention, diagnostic calculation, epidemiological calculation, variables, surveys, psychometrics, and educational framework to answer your current question (and future questions).
I am trying to bring research and statistics out of the collective unconscious and into the conscious mind where it can be effectively communicated among researchers, scientists, and students by creating this decision engine. It is easy to get to the correct research or statistical component, just answer the questions that I present you in the webpages and click on the buttons with your answer in them. Also, the step-by-step methods for conducting and interpreting each statistical test in SPSS are presented on their respective webpages.
You can also contact me via phone, social media, and email at any time in you have questions. If you need some help conducting statistics for a research project, I have eight years of experience across thousands of individual projects and I would love to help you on your study. We can negotiate prices if you are an undergraduate or graduate researcher.
In conclusion, Research Engineer makes choosing research methods and statistical tests MUCH EASIER. Just answer the questions embedded in the various decision engines and get to the correct method or test, EVERY TIME.
Thanks for your continued support, dear friends and colleagues. And many thanks and salutations to the individuals that use Research Engineer. I am honored and humbled to have this great opportunity to create a very useful and unique website. You all are the ones that make it shine!
R. Eric Heidel, Ph.D.
Assistant Professor of Biostatistics
Affiliate Professor of Biomedical Engineering
Department of Surgery
Office of Medical Education, Research, and Development
University of Tennessee Graduate School of Medicine
Owner and Operator, Scale, LLC
Scale, LLC was promoted at the event
Wife pushed for local business listing on Google
I got married yesterday to my sweet love, Jennifer Dawn Heidel. She has two great kids, Britain, 6, and Kennedy, 11. It feels great to get past another rite of passage as a man and also to marry well.
Truth be told, she had been on to me about getting Scale, LLC and Research Engineer registered as a business listing on Google for some time. I arranged for it and the letter arrived in the mail today. Try "Googling" us!
I'm getting back to my honeymoon. Thanks so much for your patronage of the blog and website!
Eric Heidel, Ph.D.
Owner and Operator
Within-subjects designs increase statistical power
Each participant serves as their own control in within-subjects designs
Within-subjects designs increase statistical power. because participants serve as their own control. Between-subjects designs necessitate more observations of the outcome to be able to effectively compare independent groups on an outcome. Multivariate analyses further decrease statistical power in that many more observations of the outcome to detect significant effects. At least 20 -40 more observations of the outcome have to collected per variable entered into a simultaneous of hierarchial regression model in order to meet statistical power when trying to account for demographic, etiological, clinical, and confounding effects.
Within-subjects designs, when coupled with with continuous outcomes, large effect sizes, limited variance in the outcome and a large sample size, greatly increase statistical power. Small effect sizes are also easier to detect using within-subjects statistics because participants serve as their own control. Within-subjects design also provide more statistical power when small sample sizes are used.
Published research in pharmacy and statistics
Two recent publications from R. Eric Heidel, Ph.D.
By day, I am an Assistant Professor of Biostatistics, Department of Surgery, University of Tennessee Graduate School of Medicine. My primary work task is to consult on resident, fellow, physician, faculty, and staff research projects and conduct statistical analyses. I also publish my own original research.
By night, I am Owner and Operator of Scalë, LLC and Research Engineer. Here are some recent publications that can further reinforce that I run a credible website with valid and relevant content. And as always, thank you for using Research Engineer!
R. Eric Heidel, Ph.D.
Pages for alpha value, beta value, Type I and Type II error, one-tailed and two-tailed tests, precision and accuracy, and inclusion and exclusion criteria
New content for Research Engineer
The following pages have been added to Research Engineer. We are dedicated here at Scale, LLC to delivering the newest and most pertinent content for you!
1. Inclusion criteria
2. Exclusion criteria
3. Precision in measurement
4. Accuracy in measurement
5. Hypothesis testing
6. Alpha value
7. Beta value
8. Type I error
9. Type II error
10. One-sided hypothesis
11. Two-sided hypothesis
Thank you for your continued use of the website! ~EH
Comparative Effectiveness Research (CER) and PPACA
New research avenues from federal legislation
The advent of the Patient Protection and Affordable Care Act (PPACA) will lead to drastic changes in the way that research is conducted to better understand healthcare outcomes of comparable treatments. The PPACA created the Patient-Centered Outcomes Research Institute (PCORI) for the purposes of bolstering and supplementing the ability of researchers to conduct Comparative Effectiveness Research (CER).
Comparative Effectiveness Research is defined in the PPACA as "research evaluation and comparing health outcomes and clinical effectiveness, risks, and benefits of two or more medical treatments, services, and items." Treatment, services, and items were defined as "healthcare interventions; protocols for treatment, care management, and delivery; procedures; medical devices; diagnostic tools; pharmaceuticals; integrative health practices; any other strategies or items being used in the treatment, management, and diagnosis, or prevention of, illness or injury in individuals."
The PPACA further set forth that the PCORI should focus on Comparative Effectiveness Research in existing clusters or subgroups of the population that are underserved or unrepresented in the current clinical literature. These clusters or subgroups tend to relate to ethnicity, gender, age, and comorbidities. These are called sensitivity analysis in that the analysis focuses strictly on these subgroups within a population.
The research designs associated with Comparative Effectiveness Research under the guise of the PPACA include randomized trials and observational designs such as prospective cohort and retrospective cohort. Randomized trials are more feasible than randomized controlled trials because the randomization occurs at the intervention level rather than the patient level. PCORI further stipulated that observational designs should meet certain benchmark criteria before valid generalizations can be made: Valid research questions, explicitly defined inclusion and exclusion criteria for participation, comparable interventions or treatments, sound secondary data sources, and transparency of treatment and analysis protocols.
Federal legislation has approved the use of observational research designs like the retrospective cohort design where data and outcomes already exist, making research much more feasible and user-friendly to conduct.
Statistical consultation and downloads
Making money from a free website is awesome
I have been running Research Engineer for close to a year now and have made some money. However, I'm still very much in the red, the learning curve is still very wide, and I'm still working hard every day to make the website better. I have put the integrity and functionality of my website ahead of making money as a tech start-up. With that being said, I offer my services as a statistical consultant at a highly competitive price and have several calculators, databases, and templates available for download. Thank you for using Research Engineer!
Eric Heidel, Ph.D. is Owner and Operator of Scalë, LLC.