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Cross-Sectional Research

Rahul Pandita
Cross-sectional research is used in different areas like psychology, business, epidemiology, etc. Let us learn some more about it in this story.
By function, this research refers to the study of a vast group of people as an observation of their behavior at the particular point of time. The result of the research forms the basis of case studies and analysis.
There is no standard definition to this concept, but it can be defined as a study of a specified group of people who vary in a certain specific variables, such as age at a particular point of time.
Its application ranges in different areas, but most widely used in the study of epidemiology, market research, and psychology. In epidemiology, the study conducted tries to establish a relationship between a disease and some traits that a specified subset of population may exhibit. Let us take a look at the purpose of its design.

Design

While conducting a cross-sectional research, the important points one needs to remember are: when to collect the information, which method is to be employed to collect data, and which mode is used to analyze the data.
The structure of the research paper depends on the type of research that needs to be carried out. Studies are categorized as pre-experimental, quasi-experimental, and true experimental. The purpose for which the research is carried out determines the design which is to be used.

Cross-Sectional Research vs. Longitudinal Research

While cross-sectional research is used to study the groups of participating population at a particular time, longitudinal research differs in the sense, that it studies the sample group over a period of time. This period of time is dependent on the type of study.
It can range from a few months to an entire life-time. Often, development researchers have to decide as to which research method will be more beneficial to them.
A longitudinal study allows a researcher to observe the developments taking place in the sample. It helps them track certain behavior and habits of the population of the sample. But, longitudinal research also comes with many disadvantages.
It takes a lot of time and effort to keep a track of a large group of population. One of the common observations in the longitudinal method is that, people tend to show completely different behavior when they are being observed or under scrutiny.
This process of research is quicker and does not require too much of capital. One also does not need to keep a track of the entire population over a period of time, as in longitudinal research. But, it lacks the in-depth analysis of longitudinal research. Let us try to understand this with the help of an example.

Cross-Sectional Research: An Example

If you visit a college and ask the students about the education standard of the college, you will only get to know the general opinion that they have of the professors, faculty, etc. This can be categorized as a cross-sectional research, as you do not know what caused them to have an opinion, whether good or bad about the college.
Longitudinal study allows you to measure the changes over a course of time. Let us take the same example as above. You visit a college and take the feedback of the faculty from a specific set of students. You then keep a track of this group of students for a period of time, say a year or two, and then you again take their feedback.
If they do not speak highly about the college, you can relate it to the reasons that might have influenced their opinions. These can be the faculty not being supportive enough or the professors being too strict in their behavior towards the students.
So, to summarize this kind of research analysis, the population at just a point of time to gather the data, whereas, longitudinal research studies the changes and their impacts on a population over a course of time.

Advantages

  • Reviews into the aspects of this research has revealed that the process involved is relatively simple and cheap, morally secure, and retrieval of data is evidently easy.
  • Comparison of data on a subject at a certain point in time.
  • Facilitates researchers to examine different variables at the same time.

Disadvantages

  • The results fetched could be very confusing.
  • The link between the cause and effect is murky.
  • The data on the subject researched is not conserved.