What method predicts an outcome variable from one predictor variable?

The method that predicts an outcome variable from one predictor variable is simple regression. This statistical technique is used to examine the linear relationship between a single independent variable (predictor) and a dependent variable (outcome). Simple regression allows researchers to determine how changes in the predictor variable are associated with changes in the outcome variable, providing a straightforward approach to understanding this relationship.

In simple regression, the analysis results in an equation that can be used to predict the value of the outcome variable based on the observed value of the predictor variable. This approach is beneficial when the goal is to establish a clear, direct connection between two variables without the complexity of additional predictor variables that may confound the relationship.

Multiple regression, while also a powerful technique for prediction, involves two or more predictor variables rather than just one. Hierarchical regression allows for the examination of the incremental value of adding predictors and is primarily used to assess the impact of additional variables on the outcome after accounting for others. Path analysis is a more complex statistical technique that explores relationships among multiple variables and is not limited to a single predictor and outcome.

Therefore, simple regression is the appropriate choice for predicting an outcome variable based solely on one predictor variable.