Cross-Sectional vs. Longitudinal Study (With Examples)
By Indeed Editorial Team
Published November 12, 2022
The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.
Researchers often use cross-sectional and longitudinal studies to record information about their subjects without manipulating the environment. These studies often differ depending on the research period. Learning the differences between cross-sectional and longitudinal studies can help you compare their benefits and purpose to choose a suitable one for conducting research. In this article, we compare the meaning of a cross-sectional vs. longitudinal study, list the elements where these studies differ, and provide examples of each.
Comparing a cross-sectional vs. longitudinal study
If you want to improve your research skills, you may benefit from comparing a cross-sectional vs. longitudinal study. Here are the definitions of each:
A cross-sectional study is a type of research where researchers collect data from various individuals during a specific period. This study describes a subject's characteristics and considers their environment. It often results in a report that records a single moment in time. For instance, researchers studying developmental psychology may use a cross-sectional study to collect and analyze the relevant data on how running may affect participants' blood sugar levels at a particular time.
Cross-sectional studies enable researchers to analyze several characteristics simultaneously, such as gender, age, and income. Researchers usually use this type of study in developmental psychology, education, epidemiology, medicine, and social sciences.
A longitudinal study is a type of research where researchers examine a group of participants repeatedly over an extended period to determine and register the potential changes. It's a type of study where researchers collect and observe data on multiple variables without influencing them. You may find this type of research study in economics, geography, social science, and medicine. Through a longitudinal study, researchers can identify changes or evolution in a target population's characteristics.
It usually provides a proven relationship between cause and effect. This study is often ideal for events that undergo transition and growth, as it may take a few weeks or years to conclude. For instance, researchers may use it to study how the human body changes during a life cycle. The following are the main types of longitudinal study:
Cohort study: This involves examining a group based on a particular event, such as geographic location or historical experience.
Panel study: It involves studying a cross-section of participants.
Retrospective study: Researchers often use this to observe past events by analyzing historical information, such as medical records.
Other differences between cross-sectional and longitudinal studies
Here are the differences between cross-sectional and longitudinal studies:
Researchers often conduct a cross-sectional study in a specific period, as they collect data to describe the events at the present moment. For instance, a researcher may collect data to determine the relationship between a participant's diet and their current cholesterol levels. By doing this, they may know if an individual's habit of eating vegetables and grains correlates with their good health conditions. A longitudinal study usually observes variables repeatedly over some time. This generally enables researchers to observe their subjects in real-time.
A sample is a group of people that a researcher uses to represent a larger population. In a cross-sectional study, researchers look at different sample groups in a population. This involves interviewing new participants each time these professionals conduct research. Cross-sectional studies enable researchers to determine how different groups of subjects react to their study environment. Some cross-sectional surveys repeat questions.
Researchers can observe how a group of individuals has changed over time when they repeat the same questions in each round. For instance, researchers may collect data on different variables to explore how age, income, educational status, and sex differences correlate with the interest rate a participant may pay on loans. A longitudinal study observes the same sample group numerous times. By doing this, researchers can follow up on subjects.
A cross-sectional study allows researchers to collect valuable information without overspending resources. These professionals can effectively collect data by using self-report surveys. A self-report survey is a poll or questionnaire in which respondents read and select answers without interference. By doing this, researchers can obtain data from multiple participants. Longitudinal studies are generally more expensive as they require researchers to collect data over a long period. They also require a certain level of commitment and resources to be effective. As longitudinal studies repeatedly observe subjects over an extended period, identifying potential insights from them may be time-consuming.
Cross-sectional studies don't provide accurate information about cause-effect relationships. This means researchers cannot use them to determine the cause of a situation. They offer results of a single moment in time and don't consider events that may occur after the research. Longitudinal research allows researchers to gain insights into cause-and-effect relationships. For instance, a cross-sectional study on the prevalence of cancer among women may give a generalized opinion that the illness often occurs in middle-aged subjects. Conversely, the longitudinal study may observe how cancer affects women when they eat certain foods or perform specific activities.
Validity determines whether a test or experiment accurately measures and represents true findings among a sample group. The cross-sectional study generally provides a valid conclusion for performing further research. For instance, suppose you want to examine the relationship between exercise and body mass. Here, you may conduct a cross-sectional study to see if there's a relationship between these variables. With this conclusion, you may use a longitudinal study to understand their relationship better.
In a longitudinal study, selective attrition may influence the validity of conclusions. Selective attrition is when some participants discontinue a study before researchers collect all the data.
Number of participants
Larger groups of participants usually provide accurate information for a study. For a cross-sectional study, researchers may use at least 60 participants to represent the population they measure. During the research, they may also measure at least three variables to develop an understanding of the relationships that exist among them. Longitudinal studies don't require a set number of participants, but it's vital a researcher uses at least one participant to measure data over time.
In a cross-sectional study, the surveys and questionnaires that researchers use to collect data from participants may not provide an accurate report. There's no mechanism these professionals can use to verify the information they collect. For longitudinal studies, researchers typically have strong and more detailed results because they can closely follow up on participants and verify the information.
Examples of cross-sectional and longitudinal studies
Here are some examples of these two types of studies:
Example of a medical study
Here's an example of a cross-sectional study in the medical field:
Some medical researchers wanted to determine the prevalence and causes of alopecia among a defined population. To do that, they evaluated individuals of different backgrounds, ages, and geographical locations. These professionals also included factors such as genetics and age. By doing this, they made conclusions, such as older individuals were more prone to have the condition.
Example of a social study
Here's an example of a cross-sectional study in the social science field:
Researchers conducted a cross-sectional study to determine how including innovative features in a laptop can promote its sales. This research aimed to validate how a laptop manufacturer can target a demographic audience. They enrolled people in different age groups and regions in the study. The conclusions showed that some individuals didn't buy a laptop with low storage. This enabled the company to modify its design and improve storage.
Example of a longitudinal study
Here's an example of a longitudinal study in the social science field:
Researchers tracked participants from childhood to adulthood to understand how growing up in a different environment influences achievement, traits, habits, and personality. They examined the identical twins for an extended period without interference. As the participants shared the same genetics, researchers assumed that any differences were the result of environmental factors.
Explore more articles
- Decision Tree Analysis: Definition and How to Perform One
- What Are Plumber Skills? (With Tips to Learn Them)
- Life Cycle Fund: Definition and How It Works (With Benefits)
- FAQ on How to Conduct Successful Staff Meetings at Work
- Enterprise Software: Definition, Benefits, and Examples
- What Is Ordinal Data? (With Reasons and Comparisons)
- What Is Contract Administration? (With Benefits and Stages)
- What Is Retention Ratio? (With Uses and Important Benefits)
- What Is Data Mining? (With Applications and Examples)
- Top 11 Machine Learning Tools (With Definition and Features)
- What Are Process Goals? (With Examples, Benefits, and Uses)
- Understanding Workflow Automation and How to Use It