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I am learning to use Python for my statistical analyses, and while figuring out how to perform a 2-way ANOVA with statsmodels I found that my Python code yielded slightly aberrant values. Comparing the outputs you can see that the SS_Factor_1 values, and the Adjusted R2 are different for Python vs SPSS/Graphpad. Is this because of a mistake in my code, or some other reason? Are these differences due to something inherent in each software and so small I should just ignore them?

Python code:

formula = 'dependent_variable ~ C(factor_1) * C(factor_2)'
model = ols(formula, data=df_freq_time).fit()
aov_table = anova_lm(model, typ=2)
aov_table

Python output: output

Also R2 = 0.722, and adj R2 = 0.694

SPSS 2-way ANOVA results: SPSS output ANOVA table

Graphpad Prism 2-way ANOVA results: Graphpad output ANOVA table

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  • $\begingroup$ Do you get the same numbers in python if you use type 3 ANOVA, typ=3? (The differences are small, but look too small for differences in definition and too large for purely numerical precision issues.) $\endgroup$
    – Josef
    Commented Sep 20, 2018 at 1:01
  • $\begingroup$ I thought it was too big a difference to be a precision issue as well. Using typ=3 gives me this output. It introduces an intercept and changes the sum of squares for all of the terms. I tried typ=1, and that just made the same output table as typ=2 but added a column for mean square values. $\endgroup$
    – user219200
    Commented Sep 20, 2018 at 4:53

1 Answer 1

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You can see that SPSS and GraphPad are the same, but your code's results are off. It's probably due to use of Type III sum-of-squares. Other things known to affect differences in SS are unbalanced sample size and missing data.

You're actually doing this the wrong way. You should be using a textbook which goes through a worked problem for a 2-way ANOVA with an interaction term and Type III SS, with intermediate calculations so you can find out where your code is making an error.

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    $\begingroup$ I might be misunderstanding your answer, but to clarify the anova_lm() function is a built-in function of the statsmodels package. I did not code it. For some reason specifying type III sum of squares (by setting typ=3) results in even stranger output, whereas the type II and III SS settings yield close to correct results. $\endgroup$
    – user219200
    Commented Sep 24, 2018 at 16:21

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