Re: [R] Use nparcomp function from nparcomp library to run post hoc

From: Dennis Murphy <djmuser_at_gmail.com>
Date: Fri, 29 Apr 2011 15:49:08 -0700

Hi:

Is this the function nparcomp() in the nparcomp package or the one from the mutoss package? When using functions from packages, it is useful to indicate the package name. I'm assuming you're using the nparcomp package, because your code worked for me when that package was loaded:

> library(nparcomp)

Loading required package: multcomp
Loading required package: mvtnorm
Loading required package: survival
Loading required package: splines

> nparcomp(Ulceration~Group,data=test,type='Dunnett',control='Non-treated')

  Nonparametric Multiple Comparison Procedure based on relative contrast effects , Type of Contrast : Dunnett  NOTE:

 *-------------------Weight Matrix------------------*

 *-----------Analysis of relative effects-----------*

 *----------------Interpretation--------------------*
 p(a,b) > 1/2 : b tends to be larger than a
 *--------------Mult.Distribution-------------------*

    < snipped for brevity - all zeros >

$Data.Info

       Sample Size
1     Duoderm   24
2     Fibrase   24

3 Kollagenase 24
4 Non-treated 24
5 Stimulen 24
6 Vehicle 24

$Analysis.of.relative.effects

                  Comparison rel.effect confidence.interval t.value
1     p(Non-treated,Duoderm)        0.5   [ 0.499 ; 0.501 ]       0
2     p(Non-treated,Fibrase)        0.5   [ 0.499 ; 0.501 ]       0
3 p(Non-treated,Kollagenase)        0.5   [ 0.499 ; 0.501 ]       0
4    p(Non-treated,Stimulen)        0.5   [ 0.499 ; 0.501 ]       0
5     p(Non-treated,Vehicle)        0.5   [ 0.499 ; 0.501 ]       0
  p.value.adjusted p.value.unadjusted
1                1                  1
2                1                  1
3                1                  1
4                1                  1
5                1                  1

$Mult.Distribution
  Quantile p.Value.global
1 2.568766 1

$Correlation
[1] NA

A graphic also appears indicating zero effect, which is what one would expect since Ulceration = 5 for every observation in the data frame.

> sessionInfo()

R version 2.13.0 (2011-04-13)
Platform: x86_64-pc-linux-gnu (64-bit)

locale:

 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
 [5] LC_MONETARY=C              LC_MESSAGES=en_US.UTF-8
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
 [9] LC_ADDRESS=C               LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

attached base packages:
[1] splines stats graphics grDevices utils datasets methods [8] base

other attached packages:
[1] nparcomp_1.0-1 multcomp_1.2-5 survival_2.36-9 mvtnorm_0.9-999 [5] sos_1.3-0 brew_1.0-6 plyr_1.5.2

loaded via a namespace (and not attached): [1] tcltk_2.13.0 tools_2.13.0

Check your version of R and the nparcomp package against this. If you have an older version of R or nparcomp, perhaps an upgrade is sufficient to fix the problem.

HTH,
Dennis

On Fri, Apr 29, 2011 at 2:49 PM, Jun Shen <jun.shen.ut_at_gmail.com> wrote:
> Dear list,

>

> I tried to use the nparcomp to run some post hoc non-parametric comparison
> and got and error.
>

> Error in uniroot(pfct, interval = interval) :
>  f() values at end points not of opposite sign
>

>  Appreciate any comments.
>

> the command line:
>
>>nparcomp(Ulceration~Group,data=test,type='Dunnett',control='Non-treated')
>
>

> Jun
> ===================================================================
> data as follows
>

> structure(list(Group = c("Duoderm", "Duoderm", "Duoderm", "Duoderm",
> "Duoderm", "Duoderm", "Duoderm", "Duoderm", "Duoderm", "Duoderm",
> "Duoderm", "Duoderm", "Duoderm", "Duoderm", "Duoderm", "Duoderm",
> "Duoderm", "Duoderm", "Duoderm", "Duoderm", "Duoderm", "Duoderm",
> "Duoderm", "Duoderm", "Fibrase", "Fibrase", "Fibrase", "Fibrase",
> "Fibrase", "Fibrase", "Fibrase", "Fibrase", "Fibrase", "Fibrase",
> "Fibrase", "Fibrase", "Fibrase", "Fibrase", "Fibrase", "Fibrase",
> "Fibrase", "Fibrase", "Fibrase", "Fibrase", "Fibrase", "Fibrase",
> "Fibrase", "Fibrase", "Kollagenase", "Kollagenase", "Kollagenase",
> "Kollagenase", "Kollagenase", "Kollagenase", "Kollagenase", "Kollagenase",
> "Kollagenase", "Kollagenase", "Kollagenase", "Kollagenase", "Kollagenase",
> "Kollagenase", "Kollagenase", "Kollagenase", "Kollagenase", "Kollagenase",
> "Kollagenase", "Kollagenase", "Kollagenase", "Kollagenase", "Kollagenase",
> "Kollagenase", "Non-treated", "Non-treated", "Non-treated", "Non-treated",
> "Non-treated", "Non-treated", "Non-treated", "Non-treated", "Non-treated",
> "Non-treated", "Non-treated", "Non-treated", "Non-treated", "Non-treated",
> "Non-treated", "Non-treated", "Non-treated", "Non-treated", "Non-treated",
> "Non-treated", "Non-treated", "Non-treated", "Non-treated", "Non-treated",
> "Stimulen", "Stimulen", "Stimulen", "Stimulen", "Stimulen", "Stimulen",
> "Stimulen", "Stimulen", "Stimulen", "Stimulen", "Stimulen", "Stimulen",
> "Stimulen", "Stimulen", "Stimulen", "Stimulen", "Stimulen", "Stimulen",
> "Stimulen", "Stimulen", "Stimulen", "Stimulen", "Stimulen", "Stimulen",
> "Vehicle", "Vehicle", "Vehicle", "Vehicle", "Vehicle", "Vehicle",
> "Vehicle", "Vehicle", "Vehicle", "Vehicle", "Vehicle", "Vehicle",
> "Vehicle", "Vehicle", "Vehicle", "Vehicle", "Vehicle", "Vehicle",
> "Vehicle", "Vehicle", "Vehicle", "Vehicle", "Vehicle", "Vehicle"
> ), Ulceration = c(5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
> 5, 5, 5), Inflamation = c(3, 4, 3, 2, 3, 3, 4, 4, 2, 2, 3, 3,
> 3, 3, 3, 3, 3, 4, 3, 3, 3, 4, 3, 3, 2, 3, 3, 4, 3, 3, 2, 4, 4,
> 4, 4, 4, 4, 4, 3, 3, 4, 3, 5, 3, 3, 4, 4, 3, 3, 2, 4, 2, 3, 3,
> 4, 3, 4, 3, 3, 4, 3, 4, 2, 3, 3, 4, 2, 3, 4, 3, 2, 3, 3, 3, 2,
> 3, 2, 2, 2, 2, 4, 3, 2, 3, 3, 4, 3, 3, 4, 3, 4, 2, 4, 3, 4, 2,
> 4, 3, 4, 3, 2, 2, 2, 2, 3, 2, 3, 2, 4, 3, 2, 4, 4, 4, 2, 2, 3,
> 3, 2, 4, 3, 2, 3, 2, 2, 2, 4, 2, 3, 2, 3, 2, 3, 3, 3, 4, 3, 3,
> 4, 4, 2, 3, 2, 3), Fibroplasia = c(4, 4, 4, 4, 4, 3, 4, 4, 4,
> 3, 4, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4, 2, 4, 4, 3,
> 2, 4, 4, 4, 4, 4, 4, 3, 3, 3, 4, 3, 3, 3, 4, 3, 4, 4, 4, 4, 4,
> 4, 4, 4, 4, 4, 4, 4, 4, 3, 4, 3, 3, 3, 4, 4, 3, 4, 4, 4, 3, 4,
> 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4,
> 4, 4, 3, 4, 4, 3, 4, 3, 2, 3, 3, 4, 3, 3, 4, 4, 3, 3, 3, 4, 3,
> 3, 4, 4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 3, 3, 4, 4, 4, 4, 4, 3, 4,
> 3, 4, 4, 4, 4, 4, 4, 4, 4), Fibrosis.and.Adexnal.Atrophy = c(4,
> 4, 4, 3, 4, 4, 4, 4, 4, 3, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
> 4, 4, 3, 4, 3, 4, 4, 3, 3, 4, 4, 4, 4, 4, 4, 4, 3, 3, 4, 3, 4,
> 4, 4, 3, 4, 3, 3, 3, 3, 3, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 3, 3,
> 4, 4, 3, 3, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4, 4, 4,
> 4, 4, 3, 4, 4, 4, 3, 4, 3, 4, 3, 4, 4, 3, 4, 3, 2, 3, 3, 4, 4,
> 3, 4, 4, 3, 3, 3, 4, 3, 3, 4, 4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 4,
> 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4), Inflammation = c(2,
> 2, 2, 1, 1, 1, 2, 3, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 2, 1,
> 1, 1, 1, 1, 1, 1, 1, 2, NA, 1, 1, 1, 2, 2, 2, 1, 2, 1, 1, 2,
> 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1,
> 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
> 1, 1, 1, 1, NA, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1,
> 2, 1, 2, 2, 1, 1, 2, 1, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 2,
> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2), Fibroplasia.1 =
> c(4,
> 4, 4, 4, 4, 3, 4, 4, 4, 3, 4, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3,
> 4, 4, 4, 4, 3, 3, 4, 3, NA, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 3,
> 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 3, 4, 3, 4, 4, 4, 4, 3,
> 3, 4, 4, 4, 3, 4, 3, 4, 4, 3, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4,
> 4, 3, 3, 3, NA, 4, 4, 4, 4, 3, 4, 3, 3, 3, 3, 3, 4, 2, 4, 3,
> 4, 4, 3, 4, 4, 2, 3, 2, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3,
> 4, 3, 3, 4, 4, 4, 4, 3, 3, 4, 3, 3, 4, 4, 4, 4, 3, 4, 4), Fibrosis = c(3,
> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
> 3, 3, 3, 3, 3, 3, 3, 3, NA, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3,
> 3, 3, 3, 3, NA, 3, 3, 3, 3, 3, 2, 2, 3, 3, 3, 3, 3, 2, 3, 3,
> 3, 3, 3, 3, 3, 2, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3,
> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3), Total = c(25,
> 26, 25, 22, 24, 22, 26, 27, 23, 21, 24, 21, 22, 23, 25, 24, 25,
> 26, 23, 23, 24, 24, 24, 24, 21, 24, 20, 24, 24, 22, 12, 25, 25,
> 25, 26, 26, 26, 24, 22, 21, 24, 22, 24, 22, 25, 23, 25, 24, 22,
> 21, 24, 21, 24, 24, 25, 23, 25, 23, 24, 24, 24, 24, 20, 21, 24,
> 26, 21, 22, 25, 23, 21, 24, 23, 24, 23, 22, 23, 23, 22, 23, 25,
> 23, 23, 24, 24, 24, 23, 22, 17, 25, 25, 21, 25, 22, 25, 19, 24,
> 23, 22, 23, 21, 16, 22, 20, 25, 22, 22, 24, 25, 19, 21, 20, 25,
> 23, 20, 22, 25, 24, 23, 25, 24, 22, 22, 21, 23, 23, 23, 20, 24,
> 23, 24, 23, 23, 22, 24, 23, 23, 24, 26, 25, 23, 23, 24, 25)), .Names =
> c("Group",
> "Ulceration", "Inflamation", "Fibroplasia", "Fibrosis.and.Adexnal.Atrophy",
> "Inflammation", "Fibroplasia.1", "Fibrosis", "Total"), row.names = c(NA,
> 144L), class = "data.frame")
>

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