Example Of A Cross Sectional Study

A cross sectional study is a cheap and easy way to gather initial data and identify correlations that can then be investigated further in a longitudinal study.

Example of a cross sectional study. The researcher can evaluate people of different ages ethnicities geographical locations and social backgrounds. Cross sectional vs longitudinal example. This is a relatively easy way to perform a preliminary experiment allowing the researcher to focus on certain population groups and understand.

Descriptive cross sectional studies the persistence and reach of a studied factor. The researcher can look at a wide range of ages ethnicities and social backgrounds. Linking the example with cross sectional study the above mentioned case is basically an example of cross sectional study where the document that was sent to the school was a basic questionnaire.

Cross sectional study example 2. Another example of a cross sectional study would be a medical study examining the prevalence of cancer amongst a defined population. An initial cross sectional study or assessment of the population can identify and remove from the cohort all active cases of the disease.

While this type of study cannot demonstrate cause and effect it can provide a quick look at correlations that may exist at a particular point. You first conduct a cross sectional study with a sample of diabetes patients to see if there are differences in health outcomes like weight or blood sugar in those who follow a low carb diet. You want to study the impact that a low carb diet has on diabetes.

A researcher might collect cross sectional data on past smoking habits and current diagnoses of lung cancer for example. This is different from analytical cross sectional studies. An example of a cross sectional study would be a medical study looking at the prevalence of breast cancer in a population.

This variation produces aanalytical reports that deal with the statistical relationship between two variables. A cross sectional study example. Our assumption is that purchasers of new cell phones with advanced features are predominantly.