How Does The Cross-Sectional Research Method Work?

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  26th Sep 2022

You might have been a subject of a survey or may have conducted a survey in your early school days. This is exactly where cross sectional data comes into play. This type of data is a study of observations involving analysis of information about a set of population at a specific time. Operating with data is given a lot of importance in the modern era. Students are thus given assignment on cross sectional data that requires a population to be surveyed. This study is majorly used for observing and analysing health status, mental status etc. of a population for example- ‘Jan-gan yojana’ or 10 year census plan.

There are two different types of Cross-Sectional Data

Analytical Studies:

• Under this type of cross sectional study, the data is investigated by the researchers between two parameters. The data is collected at a specific point of time for exposures and outcomes. This is made to calculate the relationship between exposure and the condition of the population.
• This is analytical in nature as it helps in comparing outcome differences between exposed and unexposed individuals.

Descriptive Studies:

• This type of cross sectional study is used for characterizing and assessing the different outcomes on prevalence and distribution in a defined population at a specific point of time.
• This type of study assesses that how a variable can frequently, severely or widely occurs through a demographic.

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Advantages of Cross Sectional Data

• The foremost feature is that it is swift, rapid and an easy to get your hands on study because of zero follow up requirement of subjects and it can also be done by self-report surveys.
• There is no room for error or minimal as they analyse the data that is collected by just once at a specific time, the control is maximised thus the room for mistake is minimised.
• Since it calculates multiple variables at once, it enables researchers to be able to look at numerous other characteristics i.e. age, gender, ethnicity, education and a lot more than that.

Although it is a pre-eminent source of data analysis but there are still some limitations.

Limitations of Cross Sectional Data

• There are chances that an exposure preceded disease is influenced by antecedent consequent bias.
• The presentation of information cannot be verified due to lack of credible sources. This result in hampering the data analysed because of a wrong foundation.
• The data type only assess and possess information based on a specific point of time, therefore circumstances that affects that data around that period of time is not mentioned.

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