[BioC] Help with nparLD package: Non-parametric repeated measures

Tue May 14 22:47:27 CEST 2013

Hi James,

On 5/14/2013 4:32 PM, James [guest] wrote:
> Hi,
>
> I'm trying to analyze repeated measurements of body temperature data collected from 7 randomly chosen subjects (e.g. turtles). I am using R, along with the nparLD package to test for an effect of diel period (fixed factor: day or night) and season (sub-plot fixed factor: spring, summer, fall) on body temperature.

That's a CRAN package, not a BioC package. The correct list for your 
question is r-help at r-project.org.

Best,

Jim

>
> Based on this set-up (LD-F2), I am using the non-parametric nparLD pacakge([url]http://www.inside-r.org/packages/cran/nparLD/docs/ld.f2[/url]) because data transformations were unsuccessful and I am randomly missing some paired values.
>
> 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?
>
> 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?
>
> 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]
>
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-- 
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
4225 Roosevelt Way NE, # 100
Seattle WA 98105-6099