The importance of having Large Sample Sizes for your research
Sample size can be defined as the number of pieces of information, data points or patients (in medical studies) tested or enrolled in an experiment or study. On any hypothesis, scientific research is built upon determining the mean values of a given dataset. The larger the sample size, the more accurate the average values will be. Larger sample sizes also help researchers identify outliers in data and provide smaller margins of error.
But just what is a ‘large scientific study’ with a ‘large sample size’?
Why are such studies important?
What type of research benefits most from large sample sizes?
And how can a researcher ensure they have an adequately large study?
Here, we discuss these various aspects of studies with large sample sizes.
Defining ‘large sample size’ / ‘large study’ by topic
The size of a ‘large’ study depends on the topic.
- In medicine, large studies investigating common conditions such as heart disease or cancer may enrol tens of thousands of patients with multiple years of follow-up.
- For specialty journals, ‘large studies’ may include clinical studies with hundreds of patients.
- For highly specialised topics (such as certain rare genetic conditions), large patient populations may not exist. For such research, a ‘large’ study may enrol the entire known global population with the condition, which could be as few as dozens of patients.
Statistical importance of having a large sample size
- Larger studies provide stronger and more reliable results because they have smaller margins of error and lower standards of deviation. (Standard deviation measures how spread out the data values are from the mean. The larger the study sample size, the smaller the margin of error.)
- Larger sample sizes allow researchers to control the risk of reporting false-negative or false-positive findings. The greater number of samples, the greater the precision of results will be.
A useful primer that discusses the importance of sample size in planning and interpreting medical research can be found here.
Fields that benefit most from large sample sizes
Large sample sizes benefit many fields of research, including:
- Medicine: Quality efficacy of treatment protocols, anatomic studies and biomechanical investigations all require large sample sizes. Ongoing COVID-19 vaccine trials depend on large volunteer patient populations.
- Natural sciences: Long-term climate studies, agricultural science, zoology and the like all require large studies with thousands of data points.
- Social sciences: Much social science research, public opinion and political polls, census and other demographic information, etc. rely heavily on large-scale survey studies.
Importance of a larger sample size from a publishing perspective
Academic publishers seek to publish research with the highest-quality, most-reliable and most-certain data. As an author, it is greatly to your advantage to submit manuscripts based on studies having as large a sample size as possible.
That said, there are limits to certainty and reliability of results. But that discussion would be beyond the scope of this article.
Determining an adequate sample size
In determining an adequate sample size for an experiment, you must establish the following:
- Justifiable level of statistical significance
- Chances of detecting a difference of given magnitude between the groups compared (the study’s power)
- Targeted difference (effect size)
- Variability of the data
Ensuring you have an adequately large study
Working with a biostatistician and experts familiar with study design will help you determine how large a study sample you need in order to determine a highly accurate answer to your specific hypothesis.
Note that not all research questions require massively large sample sizes. However, many do, and for such research, you may need to design, obtain funding for and conduct a multi-centre study or meta-analysis of existing studies.
Note: Multi-centre studies may come with many logistical, financial, ethical and analytical challenges. But when properly designed and executed, they provide some of the most definitive and highly cited publications.
One of the main goals of scientific research and publishing is to answer questions with as much certainty as possible. Ensuring large sample sizes in research studies would go a long way towards providing sufficient levels of certitude. Such large studies benefit numerous research applications in a wide variety of scientific and social science fields.
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