[R] R-Help: nparLD Package Non-parametric Repeated Measures

[Gerrit Eichner]

Hello, James,

see my comments inline.

> ... Main issue/question: In R the nparLD ANOVA-type Test showed a 
> significant p-value for diel period, no effect of season, and no 
> interaction between diel period and season. But a post-hoc Wilcoxon 
> Signed-Rank Test did NOT find a significant difference (p = 0.054) for 
> diel period (day vs night) body temperature.
>
> How is it possible to have a significant effect for day vs night, based on
> the nparLD package, but NO significant difference between day and night for
> the post-hoc Wilcoxon test?

Those tests -- in general -- test different hypotheses and use different 
test statistics, the first one, in addition, using a distributional 
approximation to obtain a p-value. You may want to look at the references 
cited in the respective online help pages for technical details.

> Also, if I only have two levels of the fixed effect (day vs night), do I
> need to run a post-hoc test or just look at the mean values after the
> ANOVA-type test?

Hm, actually no (of course depending on your scientific question) since 
the ANOVA-table -- if you believe its p-value -- already tells you that 
there is a (marginally) significant main "Diel-period"-effect, i.e., a 
difference between day and night.

However, I recommend that you consult with a local statistician since this 
is actually not an R-problem and since I have the impression that there 
exist some uncertainties in your statistical expertise.

  Hth  --  Gerrit

> Data info:
>
> The repeated measurements on the 7 subjects had 2 fixed effects:
>
> 1. Diel period (day or night)
> 2. Season (Spring, summer, and fall)(Subplot Factor)
>
> Mean values for body temperature and for diel period are below. Diel column
> (D=Day, N = Night). State column (RT=Spring, RF = Summer, PT = Fall).
> Subject, N=7. NA = missing value.
>
> All comments (good and bad) are greatly appreciated!
>
> Thanks,
> James
>
>
>
> -- output of sessionInfo():
>
> [code]
>> data=read.csv(file.choose(), header=TRUE)
>> attach(data)
>> data
>  stp diel state subject
> 1  26.2    D    RT       1
> 2  26.4    N    RT       1
> 3  24.1    D    RT       2
> 4    NA    N    RT       2
> 5    NA    D    RT       3
> 6  25.2    N    RT       3
> 7  27.1    D    RT       4
> 8  26.5    N    RT       4
> 9  26.9    D    RT       5
> 10 27.1    N    RT       5
> 11 26.2    D    RT       6
> 12 26.0    N    RT       6
> 13 26.3    D    RT       7
> 14 26.7    N    RT       7
> 15 26.0    D    RF       1
> 16 26.6    N    RF       1
> 17 24.2    D    RF       2
> 18 25.6    N    RF       2
> 19 25.6    D    RF       3
> 20 26.6    N    RF       3
> 21 26.1    D    RF       4
> 22 26.9    N    RF       4
> 23 27.2    D    RF       5
> 24 27.4    N    RF       5
> 25 26.2    D    RF       6
> 26 26.7    N    RF       6
> 27 27.2    D    RF       7
> 28 27.5    N    RF       7
> 29 25.0    D    PT       1
> 30 24.8    N    PT       1
> 31   NA    D    PT       2
> 32   NA    N    PT       2
> 33   NA    D    PT       3
> 34   NA    N    PT       3
> 35 26.7    D    PT       4
> 36 26.9    N    PT       4
> 37 27.6    D    PT       5
> 38 27.5    N    PT       5
> 39 25.2    D    PT       6
> 40 24.9    N    PT       6
> 41 27.1    D    PT       7
> 42 27.0    N    PT       7
>
>
>> ex.f2<-ld.f2(y=stp, time1=diel, time2=state, subject=subject,
> time1.name="Diel", time2.name="State", description=FALSE)
>
>> ex.f2$ANOVA.test
>           Statistic       df    p-value
> Diel       4.9028447 1.000000 0.02681249
> State      0.2332795 1.374320 0.70586274
> Diel:State 2.1937783 1.062943 0.13717393
> [/code]
>
> [code]
>> detach(data)
>> data=read.csv(file.choose(), header=TRUE)
>> attach(data)
>> data
>    day night
> 1  26.2  26.4
> 2  26.0  26.6
> 3  25.0  24.8
> 4  24.2  25.6
> 5  25.6  26.6
> 6  27.1  26.5
> 7  26.1  26.9
> 8  26.7  26.9
> 9  26.9  27.1
> 10 27.2  27.4
> 11 27.6  27.5
> 12 26.2  26.0
> 13 26.2  26.7
> 14 25.2  24.9
> 15 26.3  26.7
> 16 27.2  27.5
> 17 27.1  27.0
>
>> library(coin)
>
>> wilcoxsign_test(day ~ night, distribution="exact")
>
>        Exact Wilcoxon-Signed-Rank Test
>
> data:  y by x (neg, pos)
>         stratified by block
> Z = -1.9234, p-value = 0.05482
> alternative hypothesis: true mu is not equal to 0
>
> [/code]
>
> 	[[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.