> On 15 Mar 2017, at 16:32 , Leemann, Lucas T <l.leem...@essex.ac.uk> wrote:
>
> Hello,
>
> I was trying to test whether two medians are identical or not and used the
> function “mood.test” from the “stats" package. My co-author, a medical
> doctor, was trying to do the same in SPSS and had different results.
stats::mood.test() is a test of scale, not medians, according to its
documentation.
mood.medtest() is a test for a common median, basically looking at a crosstable
of observations above and below the joint median:
> M <- table(indicator, x > median(x))
> chisq.test(M)
Pearson's Chi-squared test with Yates' continuity correction
data: M
X-squared = 4.125, df = 1, p-value = 0.04225
> mood.medtest(x ~ indicator)
Mood's median test
data: x by indicator
X-squared = 4.125, df = 1, p-value = 0.04225
This might differ from SPSS output (which you do not cite) in details like
Yates correction, use of exact test, etc.
-pd
>
> I wanted to see whether there was a problem on my end and also used the
> function “mood.medtest” from the “RVAideMemoire” package. I find different
> results while I am under the impression that both functions claim to carry
> out the same test and have the same defaults. While my actual data is
> sensitive medical information, I provide simple code below for a reproducible
> example.
>
> library(RVAideMemoire)
> set.seed(123)
> a <- runif(100)
> b <- runif(120,0.2,1.1)
> indicator <- c(rep(0,100),rep(1,120))
> x <- c(a,b)
> mood.test(x ~ indicator)
> mood.medtest(x ~ indicator)
>
> Has anybody encounter this problem before or would be able to provide any
> insights?
>
> Best wishes,
> Lucas
>
>
>
>
>
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--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Office: A 4.23
Email: pd....@cbs.dk Priv: pda...@gmail.com
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