Related Experiment Video
Updated: Jun 22, 2025
07:11
Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential
Published on: May 25, 2020
6.3K
Tutorial on Biostatistics: Sample Size and Power Calculation for Ophthalmic Studies With Correlated Binary Eye
Gui-Shuang Ying1, Robert J Glynn2, Bernard Rosner2
1Center for Preventive Ophthalmology and Biostatistics, Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States.
Investigative Ophthalmology & Visual Science
|July 3, 2024
Summary
Accurate sample size and power calculations are crucial for ophthalmic studies. Accounting for intereye correlation in designs using both eyes improves efficiency and ensures reliable results.
Area of Science:
- Ophthalmology
- Biostatistics
- Clinical Trials
Background:
- Ophthalmic research frequently involves studies with binary outcomes.
- Different study designs utilize one or both eyes per subject, impacting statistical approaches.
Purpose of the Study:
- To detail and illustrate sample size and power calculations for ophthalmic studies.
- To address various common eye designs used in clinical research.
Main Methods:
- Described four eye designs: one-eye, paired, two-eye, and mixture designs.
- Demonstrated sample size and power calculations using formulas and statistical software (SAS, STATA, R, PS).
Main Results:
- Different statistical packages yield similar, though not identical, results, requiring specific parameters.
- Including both eyes per subject offers efficiency gains over one-eye designs.
- Intereye correlation must be considered for accurate calculations when using data from two eyes.
Conclusions:
- Ophthalmic study designs vary in their inclusion of one or both eyes.
- Correct sample size and power calculations are design-dependent and necessitate accounting for intereye correlation.
- Formulas and statistical software facilitate these essential calculations.
Related Concept Videos
01:15Study Design in Statistics
8.0K
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
8.0K
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
125
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
125
01:20Biostatistics: Overview
233
Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
Discrete variables are...
233
01:12Statistical Software for Data Analysis and Clinical Trials
532
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
532
01:19Overview of Biostatistics in Health Sciences
376
Biostatistics involves the application of statistical techniques to scientific research in health-related fields, including biology and public health. These techniques are essential for designing studies, collecting data, and analyzing it to draw meaningful conclusions. Given the complexity of biological processes, particularly in studies involving human subjects, biostatistical methods are crucial for effectively organizing and interpreting data that might otherwise obscure underlying patterns...
376
01:19Sample Size Calculation
3.3K
Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
3.3K