Hi Matt, see the example below. It took me a while to figure it out. I
suggest you carefully examine the example step by step. It computes t-values
for dataset with 3 variables and 8 unique combinations of two binning
variables. The code should extend easily to larger datasets. Also, it uses
the e
help@r-project.org
> Subject: Re: [R] multiple paired t-tests without loops
>
> Yes, I suspect that I will end up using a sampling approach, but I'd
> like to use an exact test if it's at all feasible.
>
> Here are two samples of data from 3 subjects:
> Sample
Hi Matthew,
First - I fully support Greg Snow proposition. Sampling is the way to go
here.
But besides that:
1) Try to avoid using data.frames as much as possible (use vectors and
matrixes instead - they are usually faster)
2) Since you are running on a loop, you can try running it in parallel (
Yes, I suspect that I will end up using a sampling approach, but I'd
like to use an exact test if it's at all feasible.
Here are two samples of data from 3 subjects:
Sample SubjC1 C2
44 1 0.0093 0.0077
44 2 0.0089 0.0069
44 3 0.051 0.0432
44 4
801.408.8111
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-
> project.org] On Behalf Of Matthew Finkbeiner
> Sent: Saturday, April 24, 2010 4:58 AM
> To: r-help@r-project.org
> Subject: [R] multiple paired t-tests without loops
>
I am new to R and I suspect my problem is easily solved, but I haven't
been able to figure it out without using loops. I am trying to
implement Blair & Karniski's (1993) permutation test. I've included a
sample data frame below. This data frame represents the conditional
means (C1, C2) for 3
I am new to R and I suspect my problem is easily solved, but I haven't
been able to figure it out without using loops. I am trying to
implement Blair & Karniski's (1993) permutation test. I've included a
sample data frame below. This data frame represents the conditional
means (C1, C2) for 3
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