In other words, this type of cross-sectional study allows us to estimate the magnitude and distribution of a phenomenon at a given time.
Generally used in the Social Sciences and Health Sciences, the transversal method can be used by other areas of knowledge.
In this article, you will find:
What is cross-sectional research?
What are the types of transversal method?
What are the characteristics of cross-sectional research?
Advantages of the transversal method
Disadvantages of the transversal method
Shall we begin?
What is cross-sectional research?
The cross-sectional method whatsapp australia is a type of observational study that analyzes data from a population at a specific time.
Also known as a prevalence study or vertical study , the objective of the cross-sectional method is to analyze the variations in the characteristics of the same sample elements (individuals, companies, organizations, among others) at a single point in time.
Cross-sectional research is generally used in health studies to understand which variables influence the occurrence of certain diseases or characteristics in a certain group.
The opposite of the cross-sectional method is the longitudinal method , which studies individuals over time.
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What are the types of transversal method?
Now that you know what cross-sectional research is, we can go a step further and understand the subtypes of this technique.
From the selection of a sample of the study population, the researcher analyzes the behavior of the predictor variable and the result variable .
In the case of observational studies in the health field, the scientist observes how the risk factor (predictor variable) and the disease (outcome variable) are related. With the results in hand, he or she can describe a health phenomenon, identify how frequently it occurs , and develop explanatory hypotheses .
What does this have to do with the type of cross-sectional study? Well, the cross-sectional method is usually divided into two types: descriptive and analytical . It all depends on whether the outcome variable is studied for its possible associations with risk factors or exposure.