Friedman test unreplicated complete block design error

Question

I'm having trouble running a Friedman test over my data. I'm trying to run a Friedman test using this command: ``` friedman.test(mean ~ isi | expId, data=monoSum) ``` On the following database (https://www.dropbox.com/s/2ox0y1b4gwld0ai/monoSum.csv): ``` > monoSum expId isi N mean 1 m80B1 1 10 100.000000 2 m80B1 2 10 73.999819 3 m80B1 3 10 45.219362 4 m80B1 4 10 116.566174 . . . . . 18 m80L2 2 10 82.945491 19 m80L2 3 10 57.675480 20 m80L2 4 10 207.169277 . . . . . . 25 m80M2 1 10 100.000000 26 m80M2 2 10 49.752687 27 m80M2 3 10 19.042592 28 m80M2 4 10 150.411035 ``` It gives me back the error: ``` Error in friedman.test.default(c(100, 73.9998193095267, 45.2193621626293, : not an unreplicated complete block design ``` I figure it gives the error because, when `monoSum$isi==1` the value of mean is always 100. Is this correct? However, `monoSum$isi==1` is alway 100 because it is the control group on which all the other `monoSum$isi` groups are normalized. I can not assume a normal distrib…

Accepted Answer

I don't get an error if I run your dataset:

```
   Friedman rank sum test

data:  mean and isi and expId
   Friedman chi-squared = 17.9143, df = 3, p-value = 0.0004581
```

However, you have to make sure that `expId` and `isi` are coded as factors. Run these commands:

```
    monoSum$expID$<-factor(monoSum$expID)
    monoSum$isi$<-factor(monoSum$isi)
```

Then run the test again. This has worked for me with a similar problem.

Friedman test unreplicated complete block design error

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