5 Differences Between Cross-Sectional, And Longitudinal Research



Research is of different types depending upon the research question. The researcher chooses a design to follow in his research. Cross-sectional and longitudinal research have different types of designs in use. The cross-sectional study goes back in time. Cross-sectional, and retrospective studies both have a different relation to time. They have different data collection, as well as analysis protocols. The longitudinal study can be in the present, or past. There are many different aspects of cross-sectional, and longitudinal studies. Some examples of these are highlighted as follows;

The Purpose Of Research Design

The purpose of a cross-sectional study design is to look at the data at a given time. It has a predefined data set. The data set may vary in the characters. But the purpose of the analysis is the event and its parameters. The CEO of the assignment writing services firm said that the purpose of a cross-sectional study is to establish the link between the event and its effect. For example, the COVID-19 pandemic affected people having low breathing rates. A cross-sectional study will provide the data sources, and analyse them for their relationships. Other studies like cohort, randomized, or even longitudinal studies need their relationships. Cross-sectional interpretations provide with a base for theoretical underpinnings of the concepts.

A longitudinal study is a repetitive event of research over time. It will analyse the data of similar events over a wide range of time. For example, a researcher wants to analyse the frequency of COVID-19 mortalities. The researcher will analyse the mortalities of all the waves. It will give a comprehensive view of indicators for the research.

The Data Collection Process

Cross-sectional studies collect data from the past, in a specific period. For example, the event has been a past activity. But the researcher decides to collect data in future. It gives an analysis of the outcomes of events too. The data collection process can be manual, or electronic. It depends upon the storage aspect of data.

The data is being collected from a specific time-lapse. It does not provide data collection for the frequency of events through a regular time interval. The study population can include humans, events, or processes. The researcher observes different groups of the population in this way. The population set might have a specific set of characters. Take for example the data from hospital records of COVID-19 admission rate in the first wave. It will provide the data of a specific event at a specific time. The researcher will be able to further analyse the findings.

In longitudinal research, the researcher collects information through more than 1 variable. The researcher in their process of data collection limits the effect on variables. The data collected will have a wide range of time in this way.

The sample set of a cross-sectional study is specific with many different types of people in one set. The longitudinal study subset has similar groups of people. The number of people is being divided among more than one group. The data analyses the variables events over time as well.

  • The longitudinal study can also collect data from the two following sources;
  • Retrospective study: Data collected from past events.
  • Prospective study: Data collected from the past but have future events implications.
  • These sources are most often used in longitudinal studies.

Time Duration Required

The time required for a cross-sectional study is less than the time needed for a longitudinal one. The cross sectionals study requires data from a specific time. It is easy to both collect, and manage. The director of an essay writing service said that the longitudinal study requires collection of data on more than one variable. The time duration of the events is also large. The typical time required for a longitudinal study is from weeks to months. Sometimes the study may take years too, in case of breakthrough research.

Examples Of Application

The examples of applications for cross-sectional study are most often in psychology. The psychological phenomenon requires specific data collection on the triggering factors. The longitudinal study has applications more often in the biological sciences. The scientific clinical drug trials of medicines also use longitudinal studies for analysis.

Let's see an example of smoking and cancer. Suppose you want to analyse that smoking has some relation with lung cancer. You will conduct a cross-sectional study in the community, or where the data is present. First, you will establish that there is a link between the two events. The relation here is that of cause and effect. Smoking is a cause, and lung cancer is an effect of the issues.

For example, you wish to perform further analysis of this theory. You have to identify how it implies in a longitudinal study. You will analyse the effect of smoking on lung cancer in different genders. The analysis will be a cohort or random control trial. It depends upon the research type. You can also use specific data collected for the cross-sectional study. You can do this by dividing the groups into similar character ones. It will help you in establishing an interpretation statement. For example, men have high smoking rates and lung cancer risks as compared to women.

Advantages Of A Cross-Sectional, And Longitudinal Study

The advantage of a cross-sectional study is that it takes less time for evaluation. The data collection processes are simple. The number of variables under this study is less. The population set is simple, and in direct relation with the variables.

Longitudinal study has the advantage of repetitive analysis. The sample size is in different groups that provide a better theoretical analysis.

There is no risk regarding biasness of the events in a longitudinal study. It provides a real-time data collection and analysis opportunity. The repetitive experiments give a chance to reanalyse the events, and to recall the experiment.


The cross-sectional longitudinal study has many differences. They establish a cause and effect relationship for the events. A cross-sectional study provides the design for identifying a problem. It studies the specific sample size with diverse characteristics. These include aspects like age and gender. It gives an analysis of the event. The longitudinal research is more discrete, with multiple variables under study. The sample groups are simple, but in groups with the ability to recall the experiment. It provides more strength to findings of the cross-sectional study.

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