I suggest you post (a shortened version of?) your tome to the
r-sig-ecology list instead.
Cheers,
Bert
On Mon, Aug 19, 2013 at 3:47 PM, Ann Marie Reinhold
<reinh...@montana.edu> wrote:
> I am running permutation regressions in package lmPerm using lmp(). I
> am getting what I find to be confusing results and I would like help
> understanding what is going on. To illustrate my problem, I created a
> simple example and am running lmp() such that the results of the lmp()
> models should be identical to that of lm(). I'm referring to the
> notes section of the lmp() documentation where it says that the
> "function will behave identically to lm() if the following parameters
> are set: perm="", seqs=TRUE, center=FALSE."
>
> Here is an example wherein I am unable to match my lmp() results to my
> lm() results.
>
> library(lmPerm)
> library(lattice)
>
> x1 <- c(rnorm(60, 150, 50),rnorm(60, 150, 50),rnorm(60, 150, 50))
> y1 <- c(30-0.1*x1[1:60], rep(10, 60), 0.1*x1[121:180])
> factor.levels1 <- c(rep("DOWN", 60), rep("FLAT", 60), rep("UP", 60))
>
> xyplot(y1 ~ x1, groups = factor.levels1, auto.key = TRUE)
>
> lmp.model.1 <- lmp(y1 ~ x1*factor.levels1 - 1, perm = "", seqs =
> TRUE, center = FALSE)
> summary(lmp.model.1)
> lm.model.1 <- lm(y1 ~ x1*factor.levels1 - 1)
> summary(lm.model.1)
>
> Here are the results:
>> summary(lmp.model.1)
> Call:
> lmp(formula = y1 ~ x1 * factor.levels1 - 1, perm = "", seqs = TRUE,
> center = FALSE)
> Residuals:
> Min 1Q Median 3Q Max
> -1.509e-13 -1.700e-16 4.277e-17 9.558e-16 1.621e-14
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> factor.levels1DOWN 3.000e+01 7.359e-15 4.077e+15 <2e-16 ***
> factor.levels1FLAT 1.000e+01 4.952e-15 2.019e+15 <2e-16 ***
> factor.levels1UP -5.809e-16 5.095e-15 -1.140e-01 0.9094
> x1 4.096e-17 2.137e-17 1.917e+00 0.0569 .
> x1:factor.levels11 -1.000e-01 3.391e-17 -2.949e+15 <2e-16 ***
> x1:factor.levels12 -4.500e-17 2.792e-17 -1.612e+00 0.1089
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> Residual standard error: 1.226e-14 on 174 degrees of freedom
> Multiple R-Squared: 1, Adjusted R-squared: 1
> F-statistic: 3.721e+31 on 6 and 174 DF, p-value: < 2.2e-16
>
>> summary(lm.model.1)
> Call:
> lm(formula = y1 ~ x1 * factor.levels1 - 1)
> Residuals:
> Min 1Q Median 3Q Max
> -3.141e-14 -3.190e-15 -9.880e-16 8.920e-16 1.905e-13
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> x1 -1.000e-01 5.638e-17 -1.774e+15 <2e-16 ***
> factor.levels1DOWN 3.000e+01 9.099e-15 3.297e+15 <2e-16 ***
> factor.levels1FLAT 1.000e+01 6.123e-15 1.633e+15 <2e-16 ***
> factor.levels1UP -3.931e-15 6.300e-15 -6.240e-01 0.533
> x1:factor.levels1FLAT 1.000e-01 6.826e-17 1.465e+15 <2e-16 ***
> x1:factor.levels1UP 2.000e-01 6.931e-17 2.886e+15 <2e-16 ***
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> Residual standard error: 1.515e-14 on 174 degrees of freedom
> Multiple R-squared: 1, Adjusted R-squared: 1
>
>
> I thought that the results of summary(lmp.model.1) would be the same
> as summary(lm.model.1). However, I am concerned that I am
> interpreting the results incorrectly because I can't get the results
> to match. Specifically, I simulated data with a slope for UP of 0.1,
> the slope for FLAT of 0, and the slope for DOWN of -0.1. I can recover
> these values in lm.model.1, but not lmp.model.1. In the output for
> the lmp.model.1, I am estimating the slope for DOWN to be
> approximately -0.1 (4.096e-17-1.000e-01) and the slope of the FLAT to
> be approximately 0 (4.096e-17-4.500e-17); however, the slope of UP
> (what I think is equal to the reference level x1) is 4.096e-17. Am I
> interpreting the x1 term incorrectly? Why are the lmp() results not
> identical to the lm() results?
>
> I ran a similar example using a modification of the above data wherein
> factor level A is equal to FLAT, factor level B is equal to DOWN, and
> factor level C is equal to UP. Again, I was unable to match the
> results from lm() and lmp().
>
> x2 <- c(rnorm(60, 150, 50), rnorm(60, 150, 50),rnorm(60, 150, 50))
> y2 <- c(rep(10, 60), 30-0.1*x2[61:120], 0.1*x2[121:180])
> factor.levels2 <- c(rep("A", 60), rep("B", 60), rep("C", 60))
>
> xyplot(y2 ~ x2, groups = factor.levels2, auto.key = TRUE)
> lmp.model.2 <- lmp(y2 ~ x2*factor.levels2 - 1, perm = "", seqs =
> TRUE, center = FALSE)
> summary(lmp.model.2)
> lm.model.2 <- lm(y2 ~ x2*factor.levels2 - 1)
> summary(lm.model.2)
>
> Here are the results:
>> summary(lmp.model.2)
> Call:
> lmp(formula = y2 ~ x2 * factor.levels2 - 1, perm = "", seqs = TRUE,
> center = FALSE)
> Residuals:
> Min 1Q Median 3Q Max
> -1.284e-13 -6.772e-16 1.439e-16 1.581e-15 4.323e-14
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> factor.levels2A 1.000e+01 5.545e-15 1.803e+15 < 2e-16 ***
> factor.levels2B 3.000e+01 4.707e-15 6.373e+15 < 2e-16 ***
> factor.levels2C 1.556e-15 4.994e-15 3.120e-01 0.755688
> x2 6.840e-17 1.860e-17 3.677e+00 0.000314 ***
> x2:factor.levels21 1.030e-16 2.734e-17 3.767e+00 0.000226 ***
> x2:factor.levels22 -1.000e-01 2.550e-17 -3.921e+15 < 2e-16 ***
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> Residual standard error: 1.131e-14 on 174 degrees of freedom
> Multiple R-Squared: 1, Adjusted R-squared: 1
> F-statistic: 4.719e+31 on 6 and 174 DF, p-value: < 2.2e-16
>
> I would expect the reference level slope (term x2 in lmp.model.2,
> which I believe is the slope for factor level C) to be 0.1. However,
> it is 6.840e-17. Am I interpreting the reference levels for the lmp()
> models incorrectly? Perhaps I am specifying the models incorrectly.
> Any help would be very much appreciated.
>
>
> My session info is as follows:
> R version 3.0.1 (2013-05-16)
> Platform: x86_64-w64-mingw32/x64 (64-bit)
> locale:
> [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
> [3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
> [5] LC_TIME=English_United States.1252
> attached base packages:
> [1] stats graphics grDevices utils datasets methods base
> other attached packages:
> [1] lattice_0.20-15 lmPerm_1.1-2
> loaded via a namespace (and not attached):
> [1] grid_3.0.1 tools_3.0.1
>
> Thanks,
> Ann Marie
>
>
>
> Ann Marie Reinhold | Doctoral Candidate
> Montana Cooperative Fishery Research Unit
> Department of Ecology | Montana State University
> Box 173460 | Bozeman, MT 59717
> Email: reinhold [AT] montana [DOT] edu | Office: (406) 994-6643
>
> ______________________________________________
> R-help@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.
--
Bert Gunter
Genentech Nonclinical Biostatistics
Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm
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