将1行实例转换为R中合适的格式以进行重复测量方差分析

Question

I'm really struggling with how to format my data to a suitable one in R.

At the moment, I have my data in the format of:

ParticipantNo | Sex | Age | IV1(0)_IV2(0)_DV1 | IV1(1)_IV2(0)_DV1 | etc

There are two levels for IV1 , and 3 for IV2 , so 6 columns per DV.

I've stacked them, so that I compare all IV1 results with each other, and the same for IV2 using a Friedman test.

However, I'd like to compare across groups like Sex and Age, and was told ANOVA is the best for this. I've used ANOVA directly before in SPSS, which accepts this data format.

The problem I have is getting this data into the correct format in R.

As I understand it, it should look like:

1 | M | 40 | IV1(0)_IV2(0)_DV1_Result

1 | M | 40 | IV1(1)_IV2(0)_DV1_Result

1 | M | 40 | IV1(0)_IV2(1)_DV1_Result

1 | M | 40 | IV1(1)_IV2(1)_DV1_Result

1 | M | 40 | IV1(0)_IV2(2)_DV1_Result

1 | M | 40 | IV1(1)_IV2(2)_DV1_Result

Then I can do aov(sex~DV1_result, data=data)

Does this seem like the correct thing to do, and if so, how can I convert from the format I have to the one I need in R?

Answer 1

Figured it out!

I used stack on my data, and then separate (ie s = separate(stack(data), "ind", c("IV1", "IV2") .

Then I could do the ANOVA by aov(values ~ IV1 * IV2, data = s)

Hope this helps someone!