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Performs a two-way analysis of variance on the data in one column of a selected fully factorial Table and reports the fixed-effects anova table in the info window.
Suppose you want to check if fundamental frequency depends on the type of vowel and speaker type. We will use the Peterson & Barney vowel data set to illustrate this. The following script will first create the data set and then produce the two-way anova report.
   Create formant table (Peterson & Barney 1952)
   Report two-way anova: "F0", "Vowel", "Type"
This will produce the following anova table in the info window:
   Two-way analysis of "F0" by "Vowel" and "Type".
   
         Source             SS        Df             MS         F         P
          Vowel        73719.4         9        8191.05    7.62537    5.25258e-11
           Type    4.18943e+06         2    2.09471e+06    1950.05              0
   Vowel x Type        6714.34        18        373.019   0.347258       0.994969
          Error    1.60053e+06      1490        1074.18
          Total    5.87039e+06      1519
The analysis shows that F0 strongly depends on the vowel and also on the speaker type and, luckily, we do not have any interaction between the vowel and the speaker type. Besides the anova table there is also shown a table with the mean F0 values for each Vowel-Type combination which looks like:
                      c         m         w      Mean
           aa       258       124       212       198
           ae       248       125       208       194
           ah       263       129       223       205
           ao       259       127       217       201
           eh       259       128       220       202
           er       264       133       219       205
           ih       270       136       232       213
           iy       270       136       231       212
           uh       273       136       234       214
           uw       278       139       235       218
         Mean       264       131       223       206
The first column of this table shows the vowel codes while the first row shows the speaker types (child, man, woman). The last row and the last column of the table shows the averages for the factors Type and Vowel, respectively. The actual data are unbalanced because we have 300, 660 and 560 replications per column respectively (for each speaker we have two replcations of the data).
The formulas to handle unbalanced designs come from Khuri (1998).
© djmw 20140117