Cross Sectional Study Analysis

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Many research projects involve studying a certain population by assessing a cross section of the group at a single point in time. Cross-sectional analysis is a useful approach to descriptive studies of a certain phenomenon or population. However, because of the limited time frame, this type of analysis requires cautious interpretation.

Identification

  • Cross-sectional studies require a researcher to take a "snapshot" -- a cross-section -- of a population at a single point in time and analyze it carefully. For example, a study of a school system's enrollment level and its demographics would be cross-sectional in nature, as the researcher would examine the number of students enrolled and their demographic characteristics, such as ethnicity and socioeconomic status, at a single point in time, such as the first day of school or the end of a grading period.

A Famous Example

  • The decennial U.S. Census, conducted by the U.S. Commerce Department's Bureau of the Census, is an example of a cross-sectional study. The census aims to paint a demographic portrait of the U.S. population at a given time. A study the size of the census requires months of work to collect data on all U.S. households. A large cross-sectional study of this nature, however, ignores such comparatively minor time differences in data collection.

Function

  • Researchers often use cross-sectional studies for descriptive purposes, such as to describe a school system's enrollment or a nation's population. However, researchers also conduct cross-sectional studies to explain certain phenomena. For example, a study of political attitudes across different age groups could survey a sample of men and women in different age groups, such as ages 18-30, 31-45, 46-65, and over 65. If the study involved only a single survey at a single point in time, it would be cross-sectional.

    Scholars in a variety of fields, including economics, education, sociology, political science, and public health, conduct cross-sectional analyses.

Considerations

  • Because the data in cross-sectional analyses are collected at a single point in time, analysts must exercise caution in drawing any conclusions about changes over time. The political attitudes study from the previous section, for example, might illustrate differing attitudes across age groups, but does not necessarily indicate changes in attitudes as a person grows older.

Prevention/Solution

  • One method for adding rigor to a basic cross-sectional study is to study the population or phenomenon of interest at multiple points in time. A researcher could strengthen the study of political attitudes, for example, by taking a sample of people in their 20s and administering a questionnaire on attitudes every five to ten years, for example, to gauge how their political views change as they age. This is known as a time series or cohort study. Another approach is to study cross-sections of multiple populations, which enables comparison. An example would be to study political attitudes among cross-sections of the people of different countries.

References

  • IInternational Encyclopedia of the Social Sciences (2nd ed.); William Darity, ed; 2007.
  • The Practice of Social Research (8th ed.), Earl Babbie, 1998
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