help with "by" function

Hi,
I have an anonymous function called function(x) that will run anova, run
HSD.test on the model, and then sort the results.  I am passing this
anonymous function to the "by" function to get results by "Isopair" factor
which is my index variable.  Since I want to run the anova on multiple
dependent variables including "Trait1" & "Trait2", I am calling the
dependent variable, "trait_names" in the model and then passing the "by"
function to another function called "funC" which takes the "trait_names" as
an argument to execute.

After I execute the funC(data_set$trait1), I am getting the results by
Isopair but the results for the two Isopairs (Isopair-A &Isopair-B) are the
same which I know is not correct.  It looks like the data is not getting
split by Isopairs and so ALL data is used in anova for both Isopairs.  Any
help in modifying function, funC or any other ways to achieve the desired
outcome will be highly appreciated.

Thanks.  Nilesh

R code, data set, and session info is pasted below.
R code:
library(agricolae)
funC<- function(trait_names){
  by(data_set, data_set$Isopair,function(x){
  mod<- aov(trait_names~ STGgroup*Field + Rep%in%Field, data=data_set)
  out<-HSD.test(mod,"STGgroup",group=TRUE,console=TRUE)
  dfout<- arrange(data.frame(out$groups),desc(trt))
  })
}
Results:
##execute funC function for Trait1 & Trait2
funC(data_set$Trait1)


data_set$Isopair: Isopair-A

      trt    means M

1 STG     776.9167 a

2 Non-STG 779.0833 a

---------------------------------------------------------------------------

data_set$Isopair: Isopair-B

      trt    means M

1 STG     776.9167 a

2 Non-STG 779.0833 a

Data:
data_set<- structure(list(Field = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L), .Label = c("LML6", "TZL2"), class = "factor"), Isopair =
structure(c(1L,
1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Isopair-A", "Isopair-B"
), class = "factor"), STGgroup = structure(c(1L, 1L, 1L, 2L,
2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L,
1L, 2L, 2L, 2L), .Label = c("Non-STG", "STG"), class = "factor"),
    Rep = structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), .Label =
c("Rep1",
    "Rep2", "Rep3"), class = "factor"), Trait1 = c(686L, 641L,
    642L, 727L, 619L, 562L, 808L, 739L, 744L, 873L, 797L, 868L,
    782L, 783L, 675L, 713L, 762L, 641L, 1009L, 995L, 845L, 1186L,
    912L, 663L), Trait2 = c(45L, 65L, 70L, 35L, 20L, 80L, 70L,
    65L, 70L, 20L, 30L, 35L, 40L, 55L, 35L, 40L, 35L, 40L, 40L,
    35L, 25L, 40L, 35L, 25L)), .Names = c("Field", "Isopair",
"STGgroup", "Rep", "Trait1", "Trait2"), class = "data.frame", row.names =
c(NA,
-24L))

Session info:

R version 3.1.3 (2015-03-09)

Platform: i386-w64-mingw32/i386 (32-bit)

Running under: Windows 7 x64 (build 7601) Service Pack 1



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] grid      stats     graphics  grDevices utils     datasets  methods
 base



other attached packages:

 [1] gridExtra_0.9.1 Hmisc_3.16-0    Formula_1.2-1   survival_2.38-1
caret_6.0-41    ggplot2_1.0.1

 [7] lattice_0.20-30 MASS_7.3-39     dplyr_0.4.1     agricolae_1.2-1



loaded via a namespace (and not attached):

 [1] acepack_1.3-3.3     assertthat_0.1      boot_1.3-15
 BradleyTerry2_1.0-6

 [5] brglm_0.5-9         car_2.0-25          cluster_2.0.1
 coda_0.17-1

 [9] codetools_0.2-10    colorspace_1.2-6    combinat_0.0-8      DBI_0.3.1

[13] deldir_0.1-9        digest_0.6.8        foreach_1.4.2
 foreign_0.8-63

[17] gtable_0.1.2        gtools_3.4.1        iterators_1.0.7
 klaR_0.6-12

[21] latticeExtra_0.6-26 lazyeval_0.1.10     LearnBayes_2.15     lme4_1.1-7

[25] magrittr_1.5        Matrix_1.1-5        mgcv_1.8-4
minqa_1.2.4

[29] munsell_0.4.2       nlme_3.1-120        nloptr_1.0.4        nnet_7.3-9

[33] parallel_3.1.3      pbkrtest_0.4-2      plyr_1.8.1
proto_0.3-10

[37] quantreg_5.11       RColorBrewer_1.1-2  Rcpp_0.11.6
 reshape2_1.4.1

[41] rpart_4.1-9         scales_0.2.4        sp_1.0-17
 SparseM_1.6

[45] spdep_0.5-88        splines_3.1.3       stringr_0.6.2
 tools_3.1.3





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