Hello,

Recently, as an explanatory aid, I analyzed data using both a regression approach and a linear approach.

As you can see, the model F-statistic is identical. However, the value (and significance) for sex has changed. I am unsure of why this has happened given that one model suggests that sex is non-significant, while the other model suggests that sex is significant. Given that ANOVA and regression are identical, I'm unsure of how to interpret the research question of whether sex is a predictor of depression.

Cheers,

David.

Recently, as an explanatory aid, I analyzed data using both a regression approach and a linear approach.

Code:

. regress depress i.sex##i.educ Source | SS df MS Number of obs = 100 -------------+---------------------------------- F(7, 92) = 1.91 Model | 15.2473617 7 2.17819453 Prob > F = 0.0761 Residual | 104.712638 92 1.13818085 R-squared = 0.1271 -------------+---------------------------------- Adj R-squared = 0.0607 Total | 119.96 99 1.21171717 Root MSE = 1.0669 ------------------------------------------------------------------------------ depress | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- 1.sex | .5714286 .7362003 0.78 0.440 -.8907288 2.033586 | educ | 2 | .7797619 .458281 1.70 0.092 -.1304237 1.689948 3 | .2751323 .4524954 0.61 0.545 -.6235627 1.173827 4 | .2987013 .515818 0.58 0.564 -.7257579 1.32316 | sex#educ | 1 2 | .4202381 .9039089 0.46 0.643 -1.375003 2.215479 1 3 | -.0251323 .8094949 -0.03 0.975 -1.632859 1.582595 1 4 | -.012987 .8989211 -0.01 0.989 -1.798322 1.772348 | _cons | 4.428571 .4032335 10.98 0.000 3.627715 5.229428 ------------------------------------------------------------------------------ . anova depress i.sex##i.educ Number of obs = 100 R-squared = 0.1271 Root MSE = 1.06686 Adj R-squared = 0.0607 Source | Partial SS df MS F Prob>F -----------+---------------------------------------------------- Model | 15.247362 7 2.1781945 1.91 0.0761 | sex | 6.7709298 1 6.7709298 5.95 0.0166 educ | 8.0498893 3 2.6832964 2.36 0.0768 sex#educ | .63825576 3 .21275192 0.19 0.9051 | Residual | 104.71264 92 1.1381809 -----------+---------------------------------------------------- Total | 119.96 99 1.2117172

**Could anyone give me an intuitive explanation for why this happens?**Cheers,

David.

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