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Growth Curve Analysis

  • Models how a response variable changes over time by fitting a mathematical function to observed data.
  • Enables description of growth patterns and prediction of future values.
  • Applied in settings such as biological growth and development of skills or behaviors.

Growth curve analysis is a statistical method used to model and analyze the growth or change in a response variable over time. It involves fitting a mathematical function to the data to describe the pattern of growth or change, and can be used to make predictions about future values of the response variable.

Growth curve analysis fits a chosen mathematical function to repeated measurements of a response variable collected over time. The fitted curve summarizes the pattern of change in the response variable and provides a basis for projecting future values. Data are typically collected at regular intervals (for example, once a week or once a month) so the model can capture the temporal trajectory of the outcome of interest.

A scientist studying the growth of a species of plant collects data on the plant’s height at regular intervals, such as once a week, and uses growth curve analysis to model the plant’s growth over time. The resulting growth curve shows how the plant’s height changes as it grows and allows predictions about future growth.

A researcher interested in the development of a child’s ability to count collects data on the child’s counting ability at regular intervals, such as once a month, and uses growth curve analysis to model the child’s progress over time. The resulting growth curve shows how the child’s counting ability changes with age and allows predictions about future progress.

  • Making predictions about future values of a response variable.
  • Identifying potential areas for intervention.
  • Identifying patterns important for understanding the underlying processes involved in growth or change.
  • Response variable
  • Mathematical function
  • Predictions