Cross-Sectional Survey Research Design

The data is used to look for patterns of association or relationships either in the group as a whole (all cases) or in subgroups sharing characteristics or...


Concept of cross sectional survey research design.

It involves the collection of quantitative data on at least two variables at one point in time (or over a short period) and from a number of cases. 

The data is used to look for patterns of association or relationships either in the group as a whole (all cases) or in subgroups sharing characteristics or attributes (females or males for example). 

Advantages of cross-sectional studies
1. Relatively inexpensive and takes up little time to conduct;
2. Can estimate prevalence of outcome of interest as sample is usually taken from the whole population;
3. Many outcomes and risk factors can be assessed;
4. Useful for public health planning, understanding disease aetiology and for the generation of hypotheses;
5. There is no loss to follow-up.

Disadvantages of cross-sectional studies
1. Difficult to make causal inference in simple statistical tests of relationships but causal inferences can be made using sophisticated techniques such as regression analyses.
2. Only a snapshot: situation may provide differing results if another time-frame had been chosen;
3. Prevalence-incidence bias (Neyman bias): a risk factor causing death will be under-represented among those with the disease.

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