Survey projects can fall into one of two main categories: longitudinal and cross-sectional.
Each one has its strengths and weaknesses, and which category is right for you will depend on what kind of data you are collecting and what kind of insights you need to glean from the results.
Let’s take a look at longitudinal and cross-sectional studies and when they work best for business.
What is the Definition of a Longitudinal Study?
A longitudinal study occurs over many touch points across an extended period of time. They are usually observational in nature. By observational, we mean that the survey makers are not interfering with the subjects or survey respondents.
The most important distinction between longitudinal and cross-sectional studies, for our purposes, is the timeline. Instead of a researcher collecting data from varying subjects in order to study the same variables, the same subjects are surveyed multiple times, in some cases, over the course of many years.
Many medical studies are longitudinal, following the same 100 individuals over the course of years. Using the same subjects in a longitudinal study allows for measurable change over a period of time to be collected.
While popular for the medical and scientific communities, longitudinal studies can have big benefits for business.
With them, you can track and measure topics as varied as:
- Market trends
- Brand awareness
- Product feedback
- Customer satisfaction
- Employee engagement
- and much more
The Three Kinds of Longitudinal Studies
There are three distinct kinds of longitudinal studies. They are:
A panel study will involve a representative sample of subjects, usually found through a panel services company.
In contrast, a cohort study observes subjects that fall in a similar group or demographic based on shared characteristics. This could include region, age, or common experience.
A retroactive study takes advantage of historical data, often times in comparison to updated data.
What is a Cross-Sectional Study?
A cross-sectional study, the not-so-distant cousin to longitudinal, is intended to compare multiple population groups at a single point in time. Instead of collecting data over time on a single variable, a cross-section is framed, allowing a researcher to see differences among population subsets in several categories.
An example would be a study on the benefits of jogging. In this study, multiple measurements are taken like resting heart rate, body mass index, and blood pressure. These would be taken all across groups of varying levels of exercise.
Researchers aren’t collecting data from a single subject over several years to learn about the effects of jogging, but from many subjects just once. This is often referred to as a ‘snapshot.’
Longitudinal and Cross-Sectional Studies: Advantages and Disadvantages
The key advantage to longitudinal studies is the ability to show the patterns of a variable over time. This is one powerful way in which we come to learn about cause-and-effect relationships. Depending on the scope of the study, longitudinal observation can also help to discover “sleeper effects” or connections between different events over a long period of time; events that might otherwise not be linked.
There are, of course, drawbacks to longitudinal studies, panel attrition being one of them. If you are dependent on the same group of 2,000 subjects for a study that takes place once every year, for twenty years, obviously some of those subjects will no longer be able to participate, either due to death, refusal, or even changes in contact information and address. That cuts down on usable data you can draw conclusions from.
Another weakness is that while longitudinal data is being collected at multiple points, those observation periods are pre-determined and cannot take into account whatever has happened in between those touch points. A third disadvantage is the idea of panel conditioning, where over time, respondents can often unknowingly change their qualitative responses to better fit what they consider to be the observer’s intended goal. The process of the study itself has changed how the subject or respondent views the questions.
Cross-sectional studies aren’t perfect either. Because of their single survey nature, they aren’t fit to make conclusive observations about the direction of any given association between variables. However, the benefits could outweigh the narrow scope disadvantages for many businesses.
For one, cross-sectional studies are affordable when compared to a similar longitudinal study. With fewer touch points (no follow up), they are also much quicker in reaching an observational conclusion. Also, provided the sample size is carefully chosen, cross-sectional studies can be helpful in representing entire populations, rather than subsets. This can be very beneficial when considering policy changes.
Logintudinal Studies vs. Cross Sectional: Which is better?
Neither, really. It all depends on what you need for your business.
The idea behind both longitudinal and cross-sectional studies is, again, to create the best process in order to collect the most useful and actionable data. One is certainly not better than the other. They both serve a very important purpose, in different ways.
The deciding factor on which you use may be the number of variables you’re trying to study, the amount of time you have before published results are expected, your budget, or, perhaps most importantly, the nature of the event you’re studying.
Ready to get started with your own study? Start a trial at Alchemer.