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Statistical testing

ANOVA or regression: how to choose

They are the same model underneath. The right choice depends on your predictors and on what your question asks.

Methodnex editorial team

Updated , 5 min read

Students are often taught ANOVA and regression in separate chapters, as if they were different methods. They are the same model. Both belong to the general linear model, and a one-way ANOVA gives exactly the same F test as a regression with dummy-coded groups. The useful question is which presentation suits your research question.

Start from the predictors

If every predictor is a category, such as treatment group or school type, and you want to compare group means, an ANOVA table is the conventional way to present the result. If at least one predictor is continuous, such as age or income, regression is the natural frame, because it estimates how much the outcome changes for each unit of the predictor.

When regression is the better choice

  • You have a mix of categorical and continuous predictors.
  • You want to adjust for covariates and report adjusted effects.
  • Groups are unequal in size or the design is unbalanced.
  • You care about the size of an effect, with a confidence interval, more than a yes or no test.

When ANOVA is the clearer presentation

  • A designed experiment with a small number of factors.
  • Readers in your field expect main effects and interactions in an ANOVA table.
  • Repeated measures on the same participants, although mixed models are now often preferred because they cope with missing observations.

Common mistakes

  • Cutting a continuous variable into groups so that ANOVA can be used. This throws away information and reduces power.
  • Running many separate t-tests in place of one model.
  • Reporting a significant F and stopping there, with no effect size and no follow-up comparisons.
  • Ignoring assumptions. Both approaches assume independent observations and residuals with roughly constant variance.

A practical rule

Write the research question first. If it asks whether group means differ, present an ANOVA and report effect sizes. If it asks how an outcome changes with one or more predictors, or needs adjustment, use regression. In both cases, check the residuals and report estimates with confidence intervals.

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