Thus it seems that there is a difference in how R/ Stata computes the interactions. I also tried to manually compute the interaction term and found something interesting: It´s the same, thus it has to do something with how the two softwares incorporate the interaction term. Here is the Stata output without the interaction: I tried to change the order of the predictor and the reference levels, but that didn´t change my R output.ĭoes anyone know what causes the difference in the F-statistic here? I´m really puzzled about it. In R it´s almost twice as high as in Stata. 11373073 1.12 0.2963Īs you can see, the F-statistics for the Group ( UW) main effect and for the Group ( UW) x trustee ( Goodguy) interaction are the same, but for the trustee ( Goodguy) main effect they differ. Null Hypothesis: There are no significant differences between groups’ mean scores. We assume that the dependent variable is normally distributed and that groups have approximately equal variance on the dependent variable. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 The One-Way ANOVA compares the mean of one or more groups based on one independent variables (or factor). STATA: Is it possible to use one-way ANOVA when the assumption of homogeneity of variances has been violated Assuming a normal distribution, can I use. Predictor 2 is also a 2 level factor called Group in R and uw in Stata. Predictor 1 is a 2-level factor called trustee in R and Goodguy in Stata Outcome variable is a continuous variable called vertrauen (=trust) Wilks’ lambda This can be interpreted as the proportion of the variance in the outcomes that is not explained by an effect. For each of the four test statistics, an F statistic and associated p-value are also displayed. The four tests are listed above the output table. To understand my output, this is my model: This One-way ANOVA Test Calculator helps you to quickly and easily produce a one-way analysis of variance (ANOVA) table that includes all relevant information from the observation data set including sums of squares, mean squares, degrees of freedom, F- and P-values. MANOVA Output In Stata, MANOVA output includes four multivariate test statistics for each predictor variable. I´m not too familiar with Stata, but as far as I understood it, I do a Type 2 SS ANOVA for both. I have run exactly the same ANOVA in both softwares, but curiously get a different F-statistics for one of the predictors. I have a question about what the difference is in how Stata and R compute ANOVAs.
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