Study population

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Study Population is a term used in Epidemiology and Statistics to refer to a specific group of individuals that are selected for a particular Research Study. The study population is a subset of the Target Population, which is the total group of individuals that the researchers are interested in studying.

Definition[edit | edit source]

A study population is defined as the group of individuals who meet specific criteria and are selected for inclusion in a research study. The criteria used to define a study population can include factors such as age, sex, health status, and geographic location. The study population is the group from which data will be collected and analyzed in the research study.

Selection of Study Population[edit | edit source]

The selection of a study population is a critical step in the design of a research study. The study population must be representative of the target population in order for the results of the study to be generalizable. This is achieved through the use of sampling techniques, which aim to select a study population that is a representative subset of the target population.

Types of Study Populations[edit | edit source]

There are several types of study populations that can be used in research studies, including:

  • Cohort: A group of individuals who share a common characteristic or experience within a defined period.
  • Case-Control: A group of individuals with a specific condition (cases) and a group of individuals without the condition (controls).
  • Cross-Sectional: A group of individuals selected without regard to their exposure or disease status.
  • Longitudinal: A group of individuals followed over time to observe changes in health or behavior.

Challenges in Defining a Study Population[edit | edit source]

Defining a study population can present several challenges. These can include:

  • Selection Bias: This occurs when the selection of individuals for the study population is not random, leading to a sample that is not representative of the target population.
  • Confounding: This occurs when an extraneous variable is associated with both the exposure and the outcome, leading to a spurious association.
  • Loss to Follow-Up: This occurs when individuals drop out of a longitudinal study, leading to incomplete data.

See Also[edit | edit source]


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Contributors: Prab R. Tumpati, MD