You should be able to calculate this from the file:

This Result File is form the Example Data. We have 2 Groups with 15 Subjects.

Sample Mean = Overall mean

The first 15 Sample Values are from group 1 the last 15 Sample Values are from Group 2 (Coresponding the design Matrix you use)

AsiNetwork 1    2 Frontal_Mid_R     to 36 Temporal_Mid_R     Test stat    4.31    Sample    mean:    0.03    Sample    subgroup    means    (according    to    design    matrix    columns):    0.05    0.01    Sample    values    :    0.002    0.392    0.001    0.005    0.001    0.103    0.003    0.146    0.003    0.003    0.003    0.005    0.004    0.003    0.131    0.003    0.002    0.005    0.005    0.002    0.002    0.002    0.006    0.002    0.002    0.002    0.002    0.006    0.001    0.105

To calculate the square root of the mean squared error (RMSE) for ANOVA1, you'll need to perform the following steps:

The first 3 Results are allready given (but rounded)

1. 
   

   Calculate the overall mean: Calculate the mean of all the sample values from both groups.

   
   
   
2. 
   

   Calculate the group means: Calculate the mean of each group's sample values separately.

   
   
   
3. 
   

   Calculate the squared deviations: Calculate the squared difference between each individual sample value and its corresponding group mean. Sum up these squared deviations.

   
   
   
4. 
   

   Calculate the mean squared error (MSE): Divide the sum of squared deviations by the total number of samples minus the number of groups.

   
   
   
5. 
   

   Calculate the square root of the mean squared error (RMSE): Take the square root of the MSE calculated in step 4.

   
   
   

Here's the calculation based on the provided data:

Sample values group 1: [0.002, 0.392, 0.001, 0.005, 0.001, 0.103, 0.003, 0.146, 0.003, 0.003, 0.003, 0.005, 0.004, 0.003, 0.131]
Sample values group 2: [0.003, 0.002, 0.005, 0.005, 0.002, 0.002, 0.002, 0.006, 0.002, 0.002, 0.002, 0.002, 0.006, 0.001, 0.105]

Overall mean: (Sum of all values) / (Total number of values) = (Sum of all values) / 30
            = (0.002 + 0.392 + ... + 0.002 + 0.105) / 30

Group 1 mean: Sum of group 1 values / Number of group 1 values
            = (0.002 + 0.392 + ... + 0.004 + 0.131) / 15

Group 2 mean: Sum of group 2 values / Number of group 2 values
            = (0.003 + 0.002 + ... + 0.006 + 0.105) / 15

Sum of squared deviations: Sum[(individual value - corresponding group mean)^2] for all values

MSE: Sum of squared deviations / (Total number of values - Number of groups)
    = Sum of squared deviations / (30 - 2)

RMSE: Square root of MSE
     = sqrt(MSE)