predict: fitted values, residuals, and prediction uncertainty

Turn the most recent fitted model into observation-level diagnostics and predictions stored as new variables.

Tested 2026-08-06 with the current stats.camp development build · View the do-file on GitHub

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Independent software. Not affiliated with, sponsored by, or endorsed by StataCorp LLC.

Complete example

clear
import delimited "data/student_scores.csv"
regress math read female
predict fitted_math
predict residual, residuals
predict fitted_se, stdp
list id math fitted_math residual fitted_se in 1/6

The first predict uses the default linear prediction. The next two request residuals and the standard error of the fitted mean.

Output from stats.camp

+--------------------------------------------------------+
|  #    id    math   fitted_math   residual   fitted_se  |
|--------------------------------------------------------|
|   1     1     45         47.82      -2.82        0.48  |
|   2     2     51         51.22      -0.22        0.66  |
|   3     3     43         42.72       0.28        0.64  |
|   4     4     56         58.86      -2.86        0.43  |
|   5     5     48         50.37      -2.37        0.42  |
|   6     6     60         62.68      -2.68        0.41  |
+--------------------------------------------------------+

What each generated variable means

fitted_math is the model's conditional mean estimate for each covariate pattern. residual is observed math minus fitted math, so observation 1 has 45 − 47.82 ≈ −2.82. fitted_se quantifies uncertainty in the fitted mean, not the spread of a future individual outcome.

Common options and current limits

The default and explicit xb create the linear prediction.
residuals, or its supported e alias, creates observed minus fitted values after a compatible model.
stdp creates the standard error of the linear prediction.
predict uses the most recent estimation result and requires a new variable name.
Official postestimation commands offer many model-specific statistics. Do not assume options beyond xb, residuals/e, and stdp are implemented here.

See the current predict entry and Stata's regress postestimation manual for an external reference.

Related guides

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