Measurement of variables has a pervasive impact on all aspects of research
The way that researchers measure for variables has a drastic impact on their ability to detect precise and accurate treatment effects. While categorical and ordinal variables are important and prevalent in empirical research, researchers must always be cognizant of the increased sample size needed to detect clinically meaningful treatment effects measured at these levels.
So, if at all possible, try to measure for predictor, confounding, and outcome variables at a continuous level because it leads to increased statistical power, increased precision and accuracy, and decreased sample size.
Click on the Scales of Measurement button to learn about categorical, nominal, ordinal, interval, ratio, count, and continuous level measurement.
Click on the Types of Variables button to learn about demographic, independent, control, dependent, predictor, confounding, and outcome variables.
Scales of measurement and types of variables
Precision and accuracy in measurement
Statistician Services for Professionals
Eric Heidel, Ph.D. will provide the following services for researchers, professionals, and organizations at $100/hour. Secure checkout is available with Stripe or PayPal.
- Statistical Analysis
- Research Design
- Sample Size Calculations
- Diagnostic Testing and Epidemiological Calculations
- Survey Design and Psychometrics
Donate to Research Engineer!
AppNotch: Convert this website into an Android and iOS app.
AppNotch team will notify you when your app gets approved in Google Play and Apple iTunes App Stores. Once your app goes live, enter your App Store URLs in this property window, publish your Weebly site and your app store icons will be visible in this page.
Please visit AppNotch.com FAQ to learn more about how to add App Store icons to your website, update your app, send Push notifications and more.
Professional Statistician For Hire!
Copyright © 2017 Scalë. All Rights Reserved. Patent Pending.