TukeyC: The TukeyC Test for Single Experiments

Description Usage Arguments Details Value Author(s) References Examples

View source: R/TukeyC.R

Description

These are methods for objects of class formula, lm, aov, aovlist and lmerMod for single, factorial, split-plot and split-split-plot experiments.

Usage

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TukeyC(x,...)

## S3 method for class 'formula'
TukeyC(formula,
       data            = NULL,
       which           = NULL,
       fl1             = NULL,
       fl2             = NULL,
       error           = NULL,
       sig.level       = .05,
       round           = 2,
       adjusted.pvalue = 'none',
       ...)

## S3 method for class 'lm'
TukeyC(x,
       which           = NULL,
       fl1             = NULL,
       fl2             = NULL,
       error           = NULL,
       sig.level       = .05,
       round           = 2,
       adjusted.pvalue = 'none',
       ...)

## S3 method for class 'aovlist'
TukeyC(x,
       which           = NULL,
       fl1             = NULL,
       fl2             = NULL,
       error           = NULL,
       sig.level       = .05,
       round           = 2,
       adjusted.pvalue = 'none',
       ...)

## S3 method for class 'lmerMod'
TukeyC(x,
       which           = NULL,
       fl1             = NULL,
       fl2             = NULL,
       error           = NULL,
       sig.level       = .05,
       round           = 2,
       adjusted.pvalue = 'none',
       ...)

Arguments

x,formula

A formula, lm, aov, aovlist and lmerMod class object. Objects of the formula class follow “response variable ~ predicted variable.

data

A object of the data.frame class. Use only objects of formula class.

which

The name of the treatment to be used in the comparison. The name must be inside quoting marks.

fl1

A vector of length 1 giving the level of the first factor in nesting order tested.

fl2

A vector of length 1 giving the level of the second factor in nesting order tested.

error

The error to be considered. If from experiment at split plot or split-split plot pay attention! See details!

sig.level

Level of Significance used in the TukeyC algorithm to create the groups of means. The default value is 0.05.

round

Integer indicating the number of decimal places.

adjusted.pvalue

Method for adjusting p values (see p.adjust to more details). The possible values are: "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr" and "none". The default is "none".

...

Potential further arguments (required by generic).

Details

The function TukeyC returns an object of class TukeyC containing the groups of means plus other necessary variables for summary and plot.

The generic functions summary and plot are used to obtain and print a summary and a plot of the results.

The error arguments may be used whenever the user want a specific error other than the experimental error. At the split plot and split-split plot experiment, combination of error may be specified with "/" in the sequence of the which argument. For example, a object of aovlist class, a possible combination would be error = 'Within/blk:plot' at case block split plot experiment with which = 'subplot:plot' argument.

Value

The function TukeyC returns a list of the class TukeyC with the slots:

Result

A data.frame storing the result of Tukey test.

Sig.level

A scalar giving the level of significance of the test.

Diff_Prob

A matrix at the lower diagonal with p-values and upper diagonal with means differences.

MSD

A matrix with minimum significance differences by Tukey methodology. If balanced data, then all values are equal.

Author(s)

Jos<e9> Cl<e1>udio Faria (joseclaudio.faria@gmail.com)
Enio Jelihovschi (eniojelihovs@gmail.com)
Ivan Bezerra Allaman (ivanalaman@gmail.com)

References

Miller, R.G. (1981) Simultaneous Statistical Inference. Springer.

Ramalho M.A.P, Ferreira D.F & Oliveira A.C. (2000) Experimenta<e7><e3>o em Gen<e9>tica e Melhoramento de Plantas. Editora UFLA.

Steel, R.G., Torrie, J.H & Dickey D.A. (1997) Principles and procedures of statistics: a biometrical approach. Third Edition.

Yandell, B.S. (1997) Practical Data Analysis for Designed Experiments. Chapman & Hall.

Examples

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##
## Examples:Randomized Complete Block Design (RCBD)
## More details: demo(package='TukeyC')
##

## The parameters can be: formula, aov, lm, aovlist and lmerMod

data(RCBD)

## From: formula
tk1 <- with(RCBD,
            TukeyC(y ~ blk + tra,
                   data=dfm,
                   which='tra'))
summary(tk1)

## From: merMod
## This class is specific of the lme4 package.
if(require(lme4)){ 
  lmer1 <- with(RCBD,
                lmer(y ~ (1|blk) + tra,
                     data=dfm))

  tk2 <-  TukeyC(lmer1,
                 which='tra')
  summary(tk2)
} 

##
## Example: Latin Squares Design (LSD)
## More details: demo(package='TukeyC')
##

data(LSD)

## From: formula
tk3 <- with(LSD,
            TukeyC(y ~ rows + cols + tra,
                   data=dfm,
                   which='tra'))
summary(tk3)

## From: aov
av1 <- with(LSD,
            aov(y ~ rows + cols + tra,
                data=dfm))

tk4 <- TukeyC(av1,
              which='tra')
summary(tk4)

## From: lm
lm1 <- with(LSD,
            lm(y ~ rows + cols + tra,
               data=dfm))

tk5 <- TukeyC(lm1,
              which='tra')
summary(tk5)

##
## Example: Factorial Experiment (FE)
## More details: demo(package='TukeyC')
##

data(FE)
## From: formula
## Main factor: N
tk6 <- with(FE,
            TukeyC(y ~ blk + N*P*K,
                   data=dfm,
                   which='N'))
summary(tk6)

## Nested: p1/N
# From: formula
n_tk1 <- with(FE,
              TukeyC(y ~ blk + N*P*K,
                     data=dfm,
                     which='P:N',
                     fl1=1))
summary(n_tk1) 

## Nested: p2/N
# From: lm
lm2 <- with(FE,
            lm(y ~ blk + N*P*K, 
               dfm))

n_tk2 <- with(FE,
              TukeyC(lm2,
                     which='P:N',
                     fl1=2))
summary(n_tk2) 

## Nested: n1/P
# From: aov
av2 <- with(FE,
            aov(y ~ blk + N*P*K,
                dfm))

n_tk3 <- with(FE,
              TukeyC(av2,
                     which='N:P',
                     fl1=1))
summary(n_tk3) 

# From: merMod
## Not run: 
if(require(lme4)){
  lmer2 <- with(FE,
                lmer(y ~ (1|blk) + N*P*K,
                     dfm))

  n_tk4 <- with(FE,
                TukeyC(lmer2,
                       which='N:P',
                       fl1=1))
  summary(n_tk4) 
}

## End(Not run)

##
## Example: Split-plot Experiment (SPET)
## More details: demo(package='TukeyC')
##
data(SPET)

## From lm
lm3 <- with(SPET,
            lm(y ~ blk*tra + tra*year,
               dfm))

# crotgrantiana/year
sp_tk1 <- TukeyC(lm3,
                 which='tra:year',
                 fl1=1)
summary(sp_tk1) 

# year1/tra
# It is necessary to set year error with trat error in the order of the "which" argument.
# It is necessary to inform how to combinate the errors
sp_tk2 <-  TukeyC(lm3,
                  which='year:tra',
                  error='Residuals/blk:tra',
                  fl1=1)
summary(sp_tk2)

# From merMod
# Onty tra
## Not run: 
if(require(lme4)){ 
  lmer3 <- with(SPET,
                lmer(y ~ blk + (1|blk:tra) + tra*year,
                     dfm))

  # comparison only tra
  sp_tk3 <- TukeyC(lmer3,
                   which = 'tra',
                   error = 'blk:tra')
  summary(sp_tk3)  

  # year1/tra
  sp_tk4 <- TukeyC(lmer3,
                   which='year:tra',
                   error='Residual/blk:tra',
                   fl1=1)
  summary(sp_tk4)
} 

## End(Not run)

## Example: Split-split-plot Experiment (SSPE)
## More details: demo(package='TukeyC')
##

data(SSPE)
## From: formula
## Main factor: P
## It is necessary to inform the appropriate error for the test
ssp_tk1 <- with(SSPE,
                TukeyC(y ~ blk + P*SP*SSP + Error(blk/P/SP),
                       data=dfm,
                       which='P',
                       error='blk:P'))
summary(ssp_tk1)

## Main factor: SP
## It is necessary to inform the appropriate error for the test
ssp_tk2 <- with(SSPE,
                TukeyC(y ~ blk + P*SP*SSP + Error(blk/P/SP),
                       data=dfm,
                       which='SP',
                       error='blk:P:SP'))
summary(ssp_tk2)

## Main factor: SSP
ssp_tk3 <- with(SSPE,
                TukeyC(y ~ blk + P*SP*SSP + Error(blk/P/SP),
                       data=dfm,
                       which='SSP'))
summary(ssp_tk3)

## From: aov
## Main factor: SSP
av3 <- with(SSPE,
            aov(y ~ blk + P*SP*SSP + Error(blk/P/SP),
                data=dfm))

ssp_tk4 <- TukeyC(av3,
                  which='SSP')
summary(ssp_tk4)

## Nested: p1/SP
## It is necessary to inform the appropriate error for the test
ssp_tk5 <- TukeyC(av3,
                  which='P:SP',
                  error='blk:P:SP',
                  fl1=1)
summary(ssp_tk5)

## Nested: p1/SSP
ssp_tk6 <- TukeyC(av3,
                  which='P:SSP',
                  fl1=1)
summary(ssp_tk6)

## Nested: p1/sp1/SSP
## Testing SSP inside of level one of P and level one of SP
ssp_tk7 <- TukeyC(av3,
                  which='P:SP:SSP',
                  fl1=1,
                  fl2=1)
summary(ssp_tk7)

## Nested: p2/sp1/SSP
ssp_tk8 <- TukeyC(av3,
                  which='P:SP:SSP',
                  fl1=2,
                  fl2=1)
summary(ssp_tk8)

## Nested: sp1/P
## It is necessary to inform the appropriate error for the test
ssp_tk9 <- TukeyC(av3,
                  which='SP:P',
                  error='blk:P:SP/blk:P',
                  fl1=1)

summary(ssp_tk9)

## Nested: ssp1/SP
ssp_tk10 <- TukeyC(av3,
                   which='SSP:SP',
                   error='Within/blk:P:SP',
                   fl1=1)
summary(ssp_tk10)

## Nested: ssp1/sp1/P
## It is necessary to inform the appropriate error for the test
ssp_tk11 <- TukeyC(av3,
                   which='SSP:SP:P',
                   error='Within/blk:P:SP/blk:P',
                   fl1=1,
                   fl2=1)
summary(ssp_tk11)

## UNBALANCED DATA
## The average are adjusted by "Least-Square-Means" methodology.
## From: formula
data(CRD2)

uCRD2 <- CRD2$dfm
uCRD2[c(3, 5, 10, 44, 45), 3] <- NA

utk1 <-  TukeyC(y ~ x,
                data=uCRD2,
                which='x')
summary(utk1)

## From: lm
ulm1 <- lm(y ~ x,
           data=uCRD2)

utk2 <- TukeyC(ulm1,
               which='x')
summary(utk2)


## Factorial Experiments
## Nested: p1/N
# From: lm

uFE <- FE$dfm
uFE[c(3, 6, 7, 20, 31, 32), 5] <- NA

ulm2 <- lm(y ~ blk + N*P*K,
           uFE)

## Nested: p1/N
utk3 <- TukeyC(ulm2,
               data=uFE,
               which='P:N',
               fl1=1)
summary(utk3) 

## Nested: p2/n2/K
utk4 <- TukeyC(ulm2,
               data=uFE,
               which='P:N:K',
               fl1=2,
               fl2=2)
summary(utk4) 

Example output

Loading required package: doBy
Goups of means at sig.level = 0.05 
   Means G1 G2
E 155.37  a   
A 142.93  a  b
D 140.40     b
B 138.57     b
C 138.56     b

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      E      A      D      B      C
E 0.000 12.438 14.975 16.795 16.805
A 0.101  0.000  2.537  4.358  4.368
D 0.039  0.978  0.000  1.820  1.830
B 0.020  0.864  0.994  0.000  0.010
C 0.020  0.863  0.993  1.000  0.000
Loading required package: lme4
Loading required package: Matrix
boundary (singular) fit: see ?isSingular
Goups of means at sig.level = 0.05 
   Means G1 G2
E 155.37  a   
A 142.93  a  b
D 140.40     b
B 138.57     b
C 138.56     b

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      E      A      D      B      C
E 0.000 12.437 14.975 16.795 16.805
A 0.115  0.000  2.538  4.358  4.368
D 0.045  0.981  0.000  1.820  1.830
B 0.022  0.879  0.994  0.000  0.010
C 0.022  0.878  0.994  1.000  0.000
Goups of means at sig.level = 0.05 
  Means G1 G2
C 60.91  a   
A 49.26     b
B 44.22     b
D 41.69     b
E 39.46     b

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      C      A      B      D      E
C 0.000 11.652 16.694 19.224 21.446
A 0.018  0.000  5.042  7.572  9.794
B 0.001  0.505  0.000  2.530  4.752
D 0.000  0.166  0.919  0.000  2.222
E 0.000  0.051  0.558  0.948  0.000
Goups of means at sig.level = 0.05 
  Means G1 G2
C 60.91  a   
A 49.26     b
B 44.22     b
D 41.69     b
E 39.46     b

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      C      A      B      D      E
C 0.000 11.652 16.694 19.224 21.446
A 0.018  0.000  5.042  7.572  9.794
B 0.001  0.505  0.000  2.530  4.752
D 0.000  0.166  0.919  0.000  2.222
E 0.000  0.051  0.558  0.948  0.000
Goups of means at sig.level = 0.05 
  Means G1 G2
C 60.91  a   
A 49.26     b
B 44.22     b
D 41.69     b
E 39.46     b

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      C      A      B      D      E
C 0.000 11.652 16.694 19.224 21.446
A 0.018  0.000  5.042  7.572  9.794
B 0.001  0.505  0.000  2.530  4.752
D 0.000  0.166  0.919  0.000  2.222
E 0.000  0.051  0.558  0.948  0.000
Goups of means at sig.level = 0.05 
   Means G1 G2
n1  2.75  a   
n0  2.31     b

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      n1    n0
n1 0.000 0.443
n0 0.006 0.000
Goups of means at sig.level = 0.05 
      Means G1
p0/n1  2.60  a
p0/n0  2.41  a

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      p0/n1 p0/n0
p0/n1 0.000 0.193
p0/n0 0.356 0.000
Goups of means at sig.level = 0.05 
      Means G1 G2
p1/n1  2.90  a   
p1/n0  2.20     b

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      p1/n1 p1/n0
p1/n1 0.000 0.694
p1/n0 0.003 0.000
Goups of means at sig.level = 0.05 
      Means G1
n0/p0  2.41  a
n0/p1  2.20  a

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      n0/p0 n0/p1
n0/p0 0.000 0.209
n0/p1 0.318 0.000
Goups of means at sig.level = 0.05 
      Means G1
n0/p0  2.41  a
n0/p1  2.20  a

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      n0/p0 n0/p1
n0/p0 0.000 0.209
n0/p1 0.731 0.000
Goups of means at sig.level = 0.05 
                Means G1 G2
crotgrantiana/2 66.60  a   
crotgrantiana/1 21.90     b

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
                crotgrantiana/2 crotgrantiana/1
crotgrantiana/2               0            44.7
crotgrantiana/1               0             0.0
Goups of means at sig.level = 0.05 
                 Means G1 G2 G3 G4
1/milho         108.75  a         
1/crotjuncea     92.50  a  b      
1/mucunapreta    83.45     b      
1/guandu         58.45        c   
1/feijaoporco    51.30        c   
1/soja           33.35           d
1/tephcandida    30.20           d
1/crotgrantiana  21.90           d

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
                1/milho 1/crotjuncea 1/mucunapreta 1/guandu 1/feijaoporco
1/milho           0.000        16.25        25.300   50.300        57.450
1/crotjuncea      0.083         0.00         9.050   34.050        41.200
1/mucunapreta     0.001         0.71         0.000   25.000        32.150
1/guandu          0.000         0.00         0.001    0.000         7.150
1/feijaoporco     0.000         0.00         0.000    0.888         0.000
1/soja            0.000         0.00         0.000    0.001         0.040
1/tephcandida     0.000         0.00         0.000    0.000         0.009
1/crotgrantiana   0.000         0.00         0.000    0.000         0.000
                1/soja 1/tephcandida 1/crotgrantiana
1/milho         75.400        78.550           86.85
1/crotjuncea    59.150        62.300           70.60
1/mucunapreta   50.100        53.250           61.55
1/guandu        25.100        28.250           36.55
1/feijaoporco   17.950        21.100           29.40
1/soja           0.000         3.150           11.45
1/tephcandida    0.999         0.000            8.30
1/crotgrantiana  0.430         0.789            0.00
Goups of means at sig.level = 0.05 
               Means G1 G2 G3 G4 G5
crotjuncea    102.55  a            
milho         100.98  a            
mucunapreta    85.82     b         
guandu         72.28        c      
feijaoporco    66.63        c      
crotgrantiana  44.25           d   
tephcandida    41.12           d  e
soja           34.53              e

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
              crotjuncea milho mucunapreta guandu feijaoporco crotgrantiana
crotjuncea         0.000 1.575      16.725 30.275      35.925        58.300
milho              0.996 0.000      15.150 28.700      34.350        56.725
mucunapreta        0.000 0.000       0.000 13.550      19.200        41.575
guandu             0.000 0.000       0.000  0.000       5.650        28.025
feijaoporco        0.000 0.000       0.000  0.259       0.000        22.375
crotgrantiana      0.000 0.000       0.000  0.000       0.000         0.000
tephcandida        0.000 0.000       0.000  0.000       0.000         0.861
soja               0.000 0.000       0.000  0.000       0.000         0.007
              tephcandida   soja
crotjuncea         61.425 68.025
milho              59.850 66.450
mucunapreta        44.700 51.300
guandu             31.150 37.750
feijaoporco        25.500 32.100
crotgrantiana       3.125  9.725
tephcandida         0.000  6.600
soja                0.125  0.000
Goups of means at sig.level = 0.05 
                 Means G1 G2 G3 G4
1/milho         108.75  a         
1/crotjuncea     92.50     b      
1/mucunapreta    83.45     b      
1/guandu         58.45        c   
1/feijaoporco    51.30        c   
1/soja           33.35           d
1/tephcandida    30.20           d
1/crotgrantiana  21.90           d

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
                1/milho 1/crotjuncea 1/mucunapreta 1/guandu 1/feijaoporco
1/milho           0.000       16.250         25.30   50.300         57.45
1/crotjuncea      0.002        0.000          9.05   34.050         41.20
1/mucunapreta     0.000        0.283          0.00   25.000         32.15
1/guandu          0.000        0.000          0.00    0.000          7.15
1/feijaoporco     0.000        0.000          0.00    0.584          0.00
1/soja            0.000        0.000          0.00    0.000          0.00
1/tephcandida     0.000        0.000          0.00    0.000          0.00
1/crotgrantiana   0.000        0.000          0.00    0.000          0.00
                1/soja 1/tephcandida 1/crotgrantiana
1/milho         75.400        78.550           86.85
1/crotjuncea    59.150        62.300           70.60
1/mucunapreta   50.100        53.250           61.55
1/guandu        25.100        28.250           36.55
1/feijaoporco   17.950        21.100           29.40
1/soja           0.000         3.150           11.45
1/tephcandida    0.991         0.000            8.30
1/crotgrantiana  0.074         0.391            0.00
Goups of means at sig.level = 0.05 
    Means G1
p2 390.00  a
p3 389.08  a
p1 387.47  a

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      p2    p3    p1
p2 0.000 0.916 2.530
p3 0.830 0.000 1.614
p1 0.303 0.580 0.000
Goups of means at sig.level = 0.05 
     Means G1
sp3 389.88  a
sp1 388.68  a
sp2 387.99  a

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      sp3   sp1   sp2
sp3 0.000 1.200 1.889
sp1 0.952 0.000 0.688
sp2 0.886 0.984 0.000
Goups of means at sig.level = 0.05 
      Means G1 G2 G3
ssp5 410.84  a      
ssp4 404.68  a  b   
ssp3 389.91  a  b   
ssp2 384.19     b   
ssp1 354.62        c

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      ssp5  ssp4   ssp3   ssp2   ssp1
ssp5 0.000 6.160 20.929 26.649 56.215
ssp4 0.965 0.000 14.769 20.489 50.055
ssp3 0.177 0.517  0.000  5.721 35.286
ssp2 0.042 0.194  0.973  0.000 29.566
ssp1 0.000 0.000  0.003  0.018  0.000
Goups of means at sig.level = 0.05 
      Means G1 G2 G3
ssp5 410.84  a      
ssp4 404.68  a  b   
ssp3 389.91  a  b   
ssp2 384.19     b   
ssp1 354.62        c

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      ssp5  ssp4   ssp3   ssp2   ssp1
ssp5 0.000 6.160 20.929 26.649 56.215
ssp4 0.965 0.000 14.769 20.489 50.055
ssp3 0.177 0.517  0.000  5.721 35.286
ssp2 0.042 0.194  0.973  0.000 29.566
ssp1 0.000 0.000  0.003  0.018  0.000
Goups of means at sig.level = 0.05 
        Means G1
p1/sp3 388.64  a
p1/sp2 387.48  a
p1/sp1 386.29  a

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
       p1/sp3 p1/sp2 p1/sp1
p1/sp3  0.000  1.159  2.350
p1/sp2  0.985  0.000  1.191
p1/sp1  0.939  0.984  0.000
Goups of means at sig.level = 0.05 
         Means G1 G2
p1/ssp5 410.92  a   
p1/ssp4 403.18  a   
p1/ssp3 388.87  a  b
p1/ssp2 382.91  a  b
p1/ssp1 351.46     b

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
        p1/ssp5 p1/ssp4 p1/ssp3 p1/ssp2 p1/ssp1
p1/ssp5   0.000   7.738  22.047  28.013  59.458
p1/ssp4   0.989   0.000  14.308  20.275  51.719
p1/ssp3   0.657   0.904   0.000   5.967  37.411
p1/ssp2   0.424   0.724   0.996   0.000  31.444
p1/ssp1   0.004   0.016   0.152   0.306   0.000
Goups of means at sig.level = 0.05 
             Means G1 G2 G3
p1/sp1/ssp5 456.35  a      
p1/sp1/ssp4 438.99  a      
p1/sp1/ssp3 392.07  a  b   
p1/sp1/ssp2 349.35     b  c
p1/sp1/ssp1 294.68        c

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
            p1/sp1/ssp5 p1/sp1/ssp4 p1/sp1/ssp3 p1/sp1/ssp2 p1/sp1/ssp1
p1/sp1/ssp5       0.000      17.365      64.278     107.000     161.670
p1/sp1/ssp4       0.972       0.000      46.913      89.635     144.305
p1/sp1/ssp3       0.158       0.459       0.000      42.723      97.392
p1/sp1/ssp2       0.002       0.016       0.553       0.000      54.670
p1/sp1/ssp1       0.000       0.000       0.007       0.302       0.000
Goups of means at sig.level = 0.05 
             Means G1 G2 G3
p2/sp1/ssp5 458.53  a      
p2/sp1/ssp4 440.07  a      
p2/sp1/ssp3 394.26  a  b   
p2/sp1/ssp2 353.65     b  c
p2/sp1/ssp1 296.61        c

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
            p2/sp1/ssp5 p2/sp1/ssp4 p2/sp1/ssp3 p2/sp1/ssp2 p2/sp1/ssp1
p2/sp1/ssp5       0.000      18.455      64.270     104.877     161.917
p2/sp1/ssp4       0.965       0.000      45.815      86.422     143.462
p2/sp1/ssp3       0.158       0.483       0.000      40.607      97.647
p2/sp1/ssp2       0.003       0.022       0.602       0.000      57.040
p2/sp1/ssp1       0.000       0.000       0.007       0.261       0.000
Goups of means at sig.level = 0.05 
        Means G1
sp1/p3 391.12  a
sp1/p2 388.63  a
sp1/p1 386.29  a

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
       sp1/p3 sp1/p2 sp1/p1
sp1/p3  0.000  2.496  4.834
sp1/p2  0.906  0.000  2.338
sp1/p1  0.695  0.917  0.000
Goups of means at sig.level = 0.05 
          Means G1 G2
ssp1/sp3 383.28  a   
ssp1/sp2 381.04  a   
ssp1/sp1 299.55     b

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
         ssp1/sp3 ssp1/sp2 ssp1/sp1
ssp1/sp3    0.000    2.238   83.725
ssp1/sp2    0.988    0.000   81.487
ssp1/sp1    0.000    0.000    0.000
Goups of means at sig.level = 0.05 
             Means G1
ssp1/sp1/p3 307.37  a
ssp1/sp1/p2 296.61  a
ssp1/sp1/p1 294.68  a

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
            ssp1/sp1/p3 ssp1/sp1/p2 ssp1/sp1/p1
ssp1/sp1/p3       0.000      10.757      12.690
ssp1/sp1/p2       0.909       0.000       1.933
ssp1/sp1/p1       0.876       0.997       0.000
Goups of means at sig.level = 0.05 
       Means G1 G2 G3 G4
tr-35 459.17  a         
tr-20 458.53  a  b      
tr-5  456.35  a  b      
tr-19 440.08  a  b      
tr-4  438.98  a  b      
tr-34 438.42  a  b      
tr-22 410.91  a  b  c   
tr-7  403.88  a  b  c   
tr-37 402.59  a  b  c   
tr-28 399.67  a  b  c  d
tr-12 398.00  a  b  c  d
tr-43 397.60  a  b  c  d
tr-13 397.50  a  b  c  d
tr-33 396.89  a  b  c  d
tr-42 394.77  a  b  c  d
tr-18 394.26  a  b  c  d
tr-27 393.32  a  b  c  d
tr-39 392.82  a  b  c  d
tr-25 392.41  a  b  c  d
tr-30 390.80  a  b  c  d
tr-10 390.20  a  b  c  d
tr-29 388.20  a  b  c  d
tr-24 387.20  a  b  c  d
tr-9  386.95  a  b  c  d
tr-15 386.21  a  b  c  d
tr-44 385.87  a  b  c  d
tr-45 385.33  a  b  c  d
tr-41 384.98  a  b  c  d
tr-2  384.71  a  b  c  d
tr-26 384.47  a  b  c  d
tr-14 383.61  a  b  c  d
tr-21 383.06  a  b  c  d
tr-36 380.75  a  b  c  d
tr-3  379.36  a  b  c  d
tr-6  379.32  a  b  c  d
tr-40 378.57  a  b  c  d
tr-38 377.35  a  b  c  d
tr-11 377.13  a  b  c  d
tr-8  377.04  a  b  c  d
tr-23 376.81  a  b  c  d
tr-32 353.76     b  c  d
tr-17 353.65     b  c  d
tr-1  311.87        c  d
tr-31 307.37        c  d
tr-16 296.61           d

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      tr-35 tr-20  tr-5  tr-19   tr-4  tr-34  tr-22   tr-7  tr-37  tr-28  tr-12
tr-35 0.000 0.635 2.815 19.090 20.180 20.743 48.255 55.285 56.572 59.497 61.162
tr-20 1.000 0.000 2.180 18.455 19.545 20.108 47.620 54.650 55.938 58.863 60.527
tr-5  1.000 1.000 0.000 16.275 17.365 17.928 45.440 52.470 53.757 56.682 58.347
tr-19 1.000 1.000 1.000  0.000  1.090  1.653 29.165 36.195 37.483 40.408 42.072
tr-4  1.000 1.000 1.000  1.000  0.000  0.562 28.075 35.105 36.392 39.317 40.982
tr-34 1.000 1.000 1.000  1.000  1.000  0.000 27.512 34.543 35.830 38.755 40.419
tr-22 0.999 0.999 1.000  1.000  1.000  1.000  0.000  7.030  8.318 11.243 12.907
tr-7  0.990 0.992 0.996  1.000  1.000  1.000  1.000  0.000  1.287  4.212  5.877
tr-37 0.985 0.988 0.994  1.000  1.000  1.000  1.000  1.000  0.000  2.925  4.589
tr-28 0.969 0.974 0.985  1.000  1.000  1.000  1.000  1.000  1.000  0.000  1.664
tr-12 0.985 0.987 0.993  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000
tr-43 0.952 0.958 0.974  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-13 0.951 0.957 0.974  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-33 0.944 0.951 0.970  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-42 0.917 0.926 0.952  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-18 0.909 0.919 0.946  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-27 0.894 0.904 0.935  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-39 0.885 0.896 0.929  0.999  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-25 0.877 0.889 0.923  0.999  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-30 0.845 0.858 0.899  0.999  0.999  0.999  1.000  1.000  1.000  1.000  1.000
tr-10 0.831 0.845 0.888  0.998  0.999  0.999  1.000  1.000  1.000  1.000  1.000
tr-29 0.783 0.799 0.849  0.997  0.998  0.998  1.000  1.000  1.000  1.000  1.000
tr-24 0.756 0.773 0.827  0.995  0.997  0.997  1.000  1.000  1.000  1.000  1.000
tr-9  0.750 0.767 0.821  0.995  0.996  0.997  1.000  1.000  1.000  1.000  1.000
tr-15 0.729 0.747 0.804  0.993  0.995  0.996  1.000  1.000  1.000  1.000  1.000
tr-44 0.720 0.737 0.795  0.993  0.995  0.996  1.000  1.000  1.000  1.000  1.000
tr-45 0.704 0.722 0.782  0.991  0.994  0.995  1.000  1.000  1.000  1.000  1.000
tr-41 0.694 0.712 0.773  0.990  0.993  0.994  1.000  1.000  1.000  1.000  1.000
tr-2  0.832 0.845 0.885  0.997  0.998  0.999  1.000  1.000  1.000  1.000  1.000
tr-26 0.679 0.697 0.759  0.989  0.992  0.993  1.000  1.000  1.000  1.000  1.000
tr-14 0.653 0.672 0.735  0.986  0.990  0.991  1.000  1.000  1.000  1.000  1.000
tr-21 0.636 0.656 0.720  0.984  0.988  0.990  1.000  1.000  1.000  1.000  1.000
tr-36 0.565 0.584 0.651  0.971  0.977  0.980  1.000  1.000  1.000  1.000  1.000
tr-3  0.703 0.720 0.775  0.987  0.990  0.992  1.000  1.000  1.000  1.000  1.000
tr-6  0.520 0.540 0.608  0.959  0.968  0.972  1.000  1.000  1.000  1.000  1.000
tr-40 0.497 0.517 0.584  0.952  0.962  0.967  1.000  1.000  1.000  1.000  1.000
tr-38 0.460 0.479 0.546  0.939  0.951  0.957  1.000  1.000  1.000  1.000  1.000
tr-11 0.641 0.659 0.718  0.977  0.982  0.985  1.000  1.000  1.000  1.000  1.000
tr-8  0.451 0.470 0.537  0.935  0.948  0.954  1.000  1.000  1.000  1.000  1.000
tr-23 0.444 0.463 0.530  0.932  0.945  0.951  1.000  1.000  1.000  1.000  1.000
tr-32 0.047 0.051 0.066  0.333  0.362  0.377  0.983  0.998  0.999  1.000  1.000
tr-17 0.047 0.051 0.066  0.330  0.359  0.374  0.983  0.998  0.999  1.000  1.000
tr-1  0.001 0.001 0.001  0.008  0.009  0.010  0.210  0.363  0.396  0.476  0.682
tr-31 0.000 0.000 0.000  0.001  0.001  0.001  0.059  0.130  0.149  0.198  0.398
tr-16 0.000 0.000 0.000  0.000  0.000  0.000  0.015  0.038  0.044  0.063  0.170
       tr-43  tr-13  tr-33  tr-42  tr-18  tr-27  tr-39  tr-25  tr-30  tr-10
tr-35 61.565 61.662 62.270 64.400 64.905 65.845 66.345 66.755 68.370 68.963
tr-20 60.930 61.028 61.635 63.765 64.270 65.210 65.710 66.120 67.735 68.328
tr-5  58.750 58.847 59.455 61.585 62.090 63.030 63.530 63.940 65.555 66.148
tr-19 42.475 42.572 43.180 45.310 45.815 46.755 47.255 47.665 49.280 49.873
tr-4  41.385 41.482 42.090 44.220 44.725 45.665 46.165 46.575 48.190 48.782
tr-34 40.822 40.920 41.528 43.657 44.162 45.102 45.602 46.012 47.627 48.220
tr-22 13.310 13.408 14.015 16.145 16.650 17.590 18.090 18.500 20.115 20.708
tr-7   6.280  6.377  6.985  9.115  9.620 10.560 11.060 11.470 13.085 13.677
tr-37  4.993  5.090  5.698  7.828  8.332  9.273  9.773 10.182 11.797 12.390
tr-28  2.068  2.165  2.773  4.903  5.407  6.348  6.848  7.257  8.873  9.465
tr-12  0.403  0.501  1.108  3.238  3.743  4.683  5.183  5.593  7.208  7.801
tr-43  0.000  0.097  0.705  2.835  3.340  4.280  4.780  5.190  6.805  7.398
tr-13  1.000  0.000  0.608  2.738  3.242  4.183  4.683  5.093  6.708  7.300
tr-33  1.000  1.000  0.000  2.130  2.635  3.575  4.075  4.485  6.100  6.692
tr-42  1.000  1.000  1.000  0.000  0.505  1.445  1.945  2.355  3.970  4.563
tr-18  1.000  1.000  1.000  1.000  0.000  0.940  1.440  1.850  3.465  4.058
tr-27  1.000  1.000  1.000  1.000  1.000  0.000  0.500  0.910  2.525  3.118
tr-39  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.410  2.025  2.618
tr-25  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000  1.615  2.208
tr-30  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.593
tr-10  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000
tr-29  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-24  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-9   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-15  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-44  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-45  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-41  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-2   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-26  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-14  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-21  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-36  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-3   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-6   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-40  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-38  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-11  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-8   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-23  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-32  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-17  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-1   0.535  0.538  0.555  0.616  0.631  0.657  0.671  0.683  0.726  0.741
tr-31  0.240  0.242  0.255  0.305  0.318  0.342  0.356  0.367  0.412  0.430
tr-16  0.080  0.081  0.087  0.110  0.116  0.128  0.135  0.140  0.165  0.175
       tr-29  tr-24   tr-9  tr-15  tr-44  tr-45  tr-41   tr-2  tr-26  tr-14
tr-35 70.968 71.970 72.215 72.960 73.298 73.833 74.183 74.455 74.697 75.558
tr-20 70.333 71.335 71.580 72.325 72.663 73.198 73.548 73.820 74.063 74.923
tr-5  68.153 69.155 69.400 70.145 70.483 71.017 71.368 71.640 71.882 72.743
tr-19 51.878 52.880 53.125 53.870 54.208 54.743 55.093 55.365 55.608 56.468
tr-4  50.787 51.790 52.035 52.780 53.117 53.652 54.002 54.275 54.517 55.377
tr-34 50.225 51.228 51.473 52.217 52.555 53.090 53.440 53.713 53.955 54.815
tr-22 22.713 23.715 23.960 24.705 25.043 25.578 25.928 26.200 26.443 27.303
tr-7  15.682 16.685 16.930 17.675 18.012 18.547 18.897 19.170 19.412 20.272
tr-37 14.395 15.398 15.643 16.387 16.725 17.260 17.610 17.883 18.125 18.985
tr-28 11.470 12.473 12.718 13.462 13.800 14.335 14.685 14.958 15.200 16.060
tr-12  9.806 10.808 11.053 11.798 12.136 12.671 13.021 13.293 13.536 14.396
tr-43  9.403 10.405 10.650 11.395 11.733 12.267 12.618 12.890 13.132 13.993
tr-13  9.305 10.308 10.553 11.298 11.635 12.170 12.520 12.793 13.035 13.895
tr-33  8.697  9.700  9.945 10.690 11.027 11.562 11.912 12.185 12.427 13.287
tr-42  6.568  7.570  7.815  8.560  8.898  9.433  9.783 10.055 10.297 11.158
tr-18  6.063  7.065  7.310  8.055  8.393  8.928  9.278  9.550  9.793 10.653
tr-27  5.123  6.125  6.370  7.115  7.453  7.988  8.338  8.610  8.852  9.713
tr-39  4.623  5.625  5.870  6.615  6.953  7.488  7.838  8.110  8.352  9.213
tr-25  4.213  5.215  5.460  6.205  6.543  7.078  7.428  7.700  7.942  8.803
tr-30  2.598  3.600  3.845  4.590  4.928  5.463  5.813  6.085  6.327  7.188
tr-10  2.005  3.007  3.253  3.997  4.335  4.870  5.220  5.493  5.735  6.595
tr-29  0.000  1.002  1.248  1.992  2.330  2.865  3.215  3.488  3.730  4.590
tr-24  1.000  0.000  0.245  0.990  1.327  1.862  2.212  2.485  2.727  3.588
tr-9   1.000  1.000  0.000  0.745  1.082  1.617  1.967  2.240  2.482  3.342
tr-15  1.000  1.000  1.000  0.000  0.338  0.873  1.223  1.495  1.738  2.598
tr-44  1.000  1.000  1.000  1.000  0.000  0.535  0.885  1.158  1.400  2.260
tr-45  1.000  1.000  1.000  1.000  1.000  0.000  0.350  0.623  0.865  1.725
tr-41  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.273  0.515  1.375
tr-2   1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.242  1.102
tr-26  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.860
tr-14  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000
tr-21  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-36  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-3   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-6   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-40  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-38  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-11  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-8   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-23  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-32  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-17  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-1   0.791  0.813  0.819  0.835  0.841  0.852  0.859  0.935  0.868  0.884
tr-31  0.490  0.521  0.528  0.552  0.562  0.579  0.590  0.766  0.606  0.632
tr-16  0.212  0.232  0.237  0.254  0.261  0.273  0.282  0.468  0.294  0.315
       tr-21  tr-36   tr-3   tr-6  tr-40  tr-38  tr-11   tr-8  tr-23   tr-32
tr-35 76.102 78.420 79.808 79.848 80.598 81.817 82.035 82.122 82.353 105.408
tr-20 75.468 77.785 79.173 79.213 79.963 81.183 81.400 81.488 81.718 104.773
tr-5  73.287 75.605 76.993 77.033 77.783 79.002 79.220 79.307 79.538 102.593
tr-19 57.013 59.330 60.718 60.758 61.508 62.728 62.945 63.033 63.263  86.318
tr-4  55.922 58.240 59.628 59.667 60.417 61.637 61.855 61.942 62.172  85.227
tr-34 55.360 57.677 59.066 59.105 59.855 61.075 61.292 61.380 61.610  84.665
tr-22 27.848 30.165 31.553 31.593 32.343 33.563 33.780 33.868 34.098  57.153
tr-7  20.817 23.135 24.523 24.563 25.312 26.532 26.750 26.837 27.068  50.123
tr-37 19.530 21.847 23.236 23.275 24.025 25.245 25.462 25.550 25.780  48.835
tr-28 16.605 18.923 20.311 20.350 21.100 22.320 22.537 22.625 22.855  45.910
tr-12 14.941 17.258 18.647 18.686 19.436 20.656 20.873 20.961 21.191  44.246
tr-43 14.537 16.855 18.243 18.283 19.033 20.252 20.470 20.557 20.788  43.843
tr-13 14.440 16.758 18.146 18.185 18.935 20.155 20.373 20.460 20.690  43.745
tr-33 13.832 16.150 17.538 17.578 18.327 19.547 19.765 19.852 20.083  43.138
tr-42 11.702 14.020 15.408 15.448 16.198 17.417 17.635 17.722 17.953  41.008
tr-18 11.198 13.515 14.903 14.943 15.693 16.913 17.130 17.218 17.448  40.503
tr-27 10.257 12.575 13.963 14.003 14.753 15.973 16.190 16.277 16.508  39.563
tr-39  9.757 12.075 13.463 13.503 14.253 15.473 15.690 15.777 16.008  39.063
tr-25  9.348 11.665 13.053 13.093 13.843 15.063 15.280 15.368 15.598  38.653
tr-30  7.733 10.050 11.438 11.478 12.228 13.448 13.665 13.752 13.983  37.038
tr-10  7.140  9.457 10.846 10.885 11.635 12.855 13.072 13.160 13.390  36.445
tr-29  5.135  7.452  8.841  8.880  9.630 10.850 11.067 11.155 11.385  34.440
tr-24  4.132  6.450  7.838  7.878  8.627  9.847 10.065 10.152 10.383  33.438
tr-9   3.887  6.205  7.593  7.633  8.382  9.602  9.820  9.907 10.138  33.192
tr-15  3.143  5.460  6.848  6.888  7.638  8.858  9.075  9.163  9.393  32.448
tr-44  2.805  5.122  6.511  6.550  7.300  8.520  8.737  8.825  9.055  32.110
tr-45  2.270  4.587  5.976  6.015  6.765  7.985  8.202  8.290  8.520  31.575
tr-41  1.920  4.237  5.626  5.665  6.415  7.635  7.852  7.940  8.170  31.225
tr-2   1.647  3.965  5.353  5.392  6.142  7.362  7.580  7.667  7.897  30.952
tr-26  1.405  3.723  5.111  5.150  5.900  7.120  7.337  7.425  7.655  30.710
tr-14  0.545  2.862  4.251  4.290  5.040  6.260  6.477  6.565  6.795  29.850
tr-21  0.000  2.317  3.706  3.745  4.495  5.715  5.932  6.020  6.250  29.305
tr-36  1.000  0.000  1.388  1.428  2.178  3.398  3.615  3.702  3.933  26.988
tr-3   1.000  1.000  0.000  0.039  0.789  2.009  2.227  2.314  2.544  25.599
tr-6   1.000  1.000  1.000  0.000  0.750  1.970  2.187  2.275  2.505  25.560
tr-40  1.000  1.000  1.000  1.000  0.000  1.220  1.437  1.525  1.755  24.810
tr-38  1.000  1.000  1.000  1.000  1.000  0.000  0.217  0.305  0.535  23.590
tr-11  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.088  0.318  23.373
tr-8   1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.230  23.285
tr-23  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000  23.055
tr-32  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000   0.000
tr-17  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000   1.000
tr-1   0.893  0.926  0.976  0.942  0.950  0.961  0.986  0.963  0.965   1.000
tr-31  0.649  0.717  0.879  0.757  0.777  0.808  0.914  0.815  0.820   1.000
tr-16  0.329  0.392  0.621  0.433  0.456  0.493  0.683  0.502  0.509   0.983
        tr-17    tr-1   tr-31   tr-16
tr-35 105.512 147.298 151.795 162.553
tr-20 104.877 146.663 151.160 161.918
tr-5  102.697 144.483 148.980 159.738
tr-19  86.422 128.208 132.705 143.463
tr-4   85.332 127.118 131.615 142.373
tr-34  84.770 126.556 131.052 141.810
tr-22  57.257  99.043 103.540 114.298
tr-7   50.227  92.013  96.510 107.268
tr-37  48.940  90.726  95.222 105.980
tr-28  46.015  87.801  92.297 103.055
tr-12  44.351  86.137  90.633 101.391
tr-43  43.947  85.733  90.230 100.988
tr-13  43.850  85.636  90.133 100.890
tr-33  43.242  85.028  89.525 100.283
tr-42  41.112  82.898  87.395  98.153
tr-18  40.608  82.393  86.890  97.648
tr-27  39.667  81.453  85.950  96.708
tr-39  39.167  80.953  85.450  96.208
tr-25  38.757  80.543  85.040  95.798
tr-30  37.142  78.928  83.425  94.183
tr-10  36.550  78.336  82.832  93.590
tr-29  34.545  76.331  80.827  91.585
tr-24  33.542  75.328  79.825  90.583
tr-9   33.297  75.083  79.580  90.338
tr-15  32.552  74.338  78.835  89.593
tr-44  32.215  74.001  78.497  89.255
tr-45  31.680  73.466  77.962  88.720
tr-41  31.330  73.116  77.612  88.370
tr-2   31.057  72.843  77.340  88.097
tr-26  30.815  72.601  77.097  87.855
tr-14  29.955  71.741  76.237  86.995
tr-21  29.410  71.196  75.692  86.450
tr-36  27.092  68.878  73.375  84.133
tr-3   25.704  67.490  71.987  82.744
tr-6   25.665  67.451  71.947  82.705
tr-40  24.915  66.701  71.197  81.955
tr-38  23.695  65.481  69.977  80.735
tr-11  23.477  65.263  69.760  80.518
tr-8   23.390  65.176  69.672  80.430
tr-23  23.160  64.946  69.442  80.200
tr-32   0.105  41.891  46.387  57.145
tr-17   0.000  41.786  46.283  57.040
tr-1    1.000   0.000   4.497  15.254
tr-31   1.000   1.000   0.000  10.758
tr-16   0.984   1.000   1.000   0.000
Goups of means at sig.level = 0.05 
       Means G1 G2 G3 G4
tr-35 459.17  a         
tr-20 458.53  a  b      
tr-5  456.35  a  b      
tr-19 440.08  a  b      
tr-4  438.98  a  b      
tr-34 438.42  a  b      
tr-22 410.91  a  b  c   
tr-7  403.88  a  b  c   
tr-37 402.59  a  b  c   
tr-28 399.67  a  b  c  d
tr-12 398.00  a  b  c  d
tr-43 397.60  a  b  c  d
tr-13 397.50  a  b  c  d
tr-33 396.89  a  b  c  d
tr-42 394.77  a  b  c  d
tr-18 394.26  a  b  c  d
tr-27 393.32  a  b  c  d
tr-39 392.82  a  b  c  d
tr-25 392.41  a  b  c  d
tr-30 390.80  a  b  c  d
tr-10 390.20  a  b  c  d
tr-29 388.20  a  b  c  d
tr-24 387.20  a  b  c  d
tr-9  386.95  a  b  c  d
tr-15 386.21  a  b  c  d
tr-44 385.87  a  b  c  d
tr-45 385.33  a  b  c  d
tr-41 384.98  a  b  c  d
tr-2  384.71  a  b  c  d
tr-26 384.47  a  b  c  d
tr-14 383.61  a  b  c  d
tr-21 383.06  a  b  c  d
tr-36 380.75  a  b  c  d
tr-3  379.36  a  b  c  d
tr-6  379.32  a  b  c  d
tr-40 378.57  a  b  c  d
tr-38 377.35  a  b  c  d
tr-11 377.13  a  b  c  d
tr-8  377.04  a  b  c  d
tr-23 376.81  a  b  c  d
tr-32 353.76     b  c  d
tr-17 353.65     b  c  d
tr-1  311.87        c  d
tr-31 307.37        c  d
tr-16 296.61           d

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      tr-35 tr-20  tr-5  tr-19   tr-4  tr-34  tr-22   tr-7  tr-37  tr-28  tr-12
tr-35 0.000 0.635 2.815 19.090 20.180 20.743 48.255 55.285 56.572 59.497 61.162
tr-20 1.000 0.000 2.180 18.455 19.545 20.108 47.620 54.650 55.938 58.863 60.527
tr-5  1.000 1.000 0.000 16.275 17.365 17.928 45.440 52.470 53.757 56.682 58.347
tr-19 1.000 1.000 1.000  0.000  1.090  1.653 29.165 36.195 37.483 40.408 42.072
tr-4  1.000 1.000 1.000  1.000  0.000  0.562 28.075 35.105 36.392 39.317 40.982
tr-34 1.000 1.000 1.000  1.000  1.000  0.000 27.512 34.543 35.830 38.755 40.419
tr-22 0.999 0.999 1.000  1.000  1.000  1.000  0.000  7.030  8.318 11.243 12.907
tr-7  0.990 0.992 0.996  1.000  1.000  1.000  1.000  0.000  1.287  4.212  5.877
tr-37 0.985 0.988 0.994  1.000  1.000  1.000  1.000  1.000  0.000  2.925  4.589
tr-28 0.969 0.974 0.985  1.000  1.000  1.000  1.000  1.000  1.000  0.000  1.664
tr-12 0.985 0.987 0.993  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000
tr-43 0.952 0.958 0.974  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-13 0.951 0.957 0.974  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-33 0.944 0.951 0.970  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-42 0.917 0.926 0.952  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-18 0.909 0.919 0.946  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-27 0.894 0.904 0.935  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-39 0.885 0.896 0.929  0.999  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-25 0.877 0.889 0.923  0.999  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-30 0.845 0.858 0.899  0.999  0.999  0.999  1.000  1.000  1.000  1.000  1.000
tr-10 0.831 0.845 0.888  0.998  0.999  0.999  1.000  1.000  1.000  1.000  1.000
tr-29 0.783 0.799 0.849  0.997  0.998  0.998  1.000  1.000  1.000  1.000  1.000
tr-24 0.756 0.773 0.827  0.995  0.997  0.997  1.000  1.000  1.000  1.000  1.000
tr-9  0.750 0.767 0.821  0.995  0.996  0.997  1.000  1.000  1.000  1.000  1.000
tr-15 0.729 0.747 0.804  0.993  0.995  0.996  1.000  1.000  1.000  1.000  1.000
tr-44 0.720 0.737 0.795  0.993  0.995  0.996  1.000  1.000  1.000  1.000  1.000
tr-45 0.704 0.722 0.782  0.991  0.994  0.995  1.000  1.000  1.000  1.000  1.000
tr-41 0.694 0.712 0.773  0.990  0.993  0.994  1.000  1.000  1.000  1.000  1.000
tr-2  0.832 0.845 0.885  0.997  0.998  0.999  1.000  1.000  1.000  1.000  1.000
tr-26 0.679 0.697 0.759  0.989  0.992  0.993  1.000  1.000  1.000  1.000  1.000
tr-14 0.653 0.672 0.735  0.986  0.990  0.991  1.000  1.000  1.000  1.000  1.000
tr-21 0.636 0.656 0.720  0.984  0.988  0.990  1.000  1.000  1.000  1.000  1.000
tr-36 0.565 0.584 0.651  0.971  0.977  0.980  1.000  1.000  1.000  1.000  1.000
tr-3  0.703 0.720 0.775  0.987  0.990  0.992  1.000  1.000  1.000  1.000  1.000
tr-6  0.520 0.540 0.608  0.959  0.968  0.972  1.000  1.000  1.000  1.000  1.000
tr-40 0.497 0.517 0.584  0.952  0.962  0.967  1.000  1.000  1.000  1.000  1.000
tr-38 0.460 0.479 0.546  0.939  0.951  0.957  1.000  1.000  1.000  1.000  1.000
tr-11 0.641 0.659 0.718  0.977  0.982  0.985  1.000  1.000  1.000  1.000  1.000
tr-8  0.451 0.470 0.537  0.935  0.948  0.954  1.000  1.000  1.000  1.000  1.000
tr-23 0.444 0.463 0.530  0.932  0.945  0.951  1.000  1.000  1.000  1.000  1.000
tr-32 0.047 0.051 0.066  0.333  0.362  0.377  0.983  0.998  0.999  1.000  1.000
tr-17 0.047 0.051 0.066  0.330  0.359  0.374  0.983  0.998  0.999  1.000  1.000
tr-1  0.001 0.001 0.001  0.008  0.009  0.010  0.210  0.363  0.396  0.476  0.682
tr-31 0.000 0.000 0.000  0.001  0.001  0.001  0.059  0.130  0.149  0.198  0.398
tr-16 0.000 0.000 0.000  0.000  0.000  0.000  0.015  0.038  0.044  0.063  0.170
       tr-43  tr-13  tr-33  tr-42  tr-18  tr-27  tr-39  tr-25  tr-30  tr-10
tr-35 61.565 61.662 62.270 64.400 64.905 65.845 66.345 66.755 68.370 68.963
tr-20 60.930 61.028 61.635 63.765 64.270 65.210 65.710 66.120 67.735 68.328
tr-5  58.750 58.847 59.455 61.585 62.090 63.030 63.530 63.940 65.555 66.148
tr-19 42.475 42.572 43.180 45.310 45.815 46.755 47.255 47.665 49.280 49.873
tr-4  41.385 41.482 42.090 44.220 44.725 45.665 46.165 46.575 48.190 48.782
tr-34 40.822 40.920 41.528 43.657 44.162 45.102 45.602 46.012 47.627 48.220
tr-22 13.310 13.408 14.015 16.145 16.650 17.590 18.090 18.500 20.115 20.708
tr-7   6.280  6.377  6.985  9.115  9.620 10.560 11.060 11.470 13.085 13.677
tr-37  4.993  5.090  5.698  7.828  8.332  9.273  9.773 10.182 11.797 12.390
tr-28  2.068  2.165  2.773  4.903  5.407  6.348  6.848  7.257  8.873  9.465
tr-12  0.403  0.501  1.108  3.238  3.743  4.683  5.183  5.593  7.208  7.801
tr-43  0.000  0.097  0.705  2.835  3.340  4.280  4.780  5.190  6.805  7.398
tr-13  1.000  0.000  0.608  2.738  3.242  4.183  4.683  5.093  6.708  7.300
tr-33  1.000  1.000  0.000  2.130  2.635  3.575  4.075  4.485  6.100  6.692
tr-42  1.000  1.000  1.000  0.000  0.505  1.445  1.945  2.355  3.970  4.563
tr-18  1.000  1.000  1.000  1.000  0.000  0.940  1.440  1.850  3.465  4.058
tr-27  1.000  1.000  1.000  1.000  1.000  0.000  0.500  0.910  2.525  3.118
tr-39  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.410  2.025  2.618
tr-25  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000  1.615  2.208
tr-30  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.593
tr-10  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000
tr-29  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-24  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-9   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-15  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-44  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-45  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-41  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-2   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-26  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-14  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-21  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-36  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-3   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-6   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-40  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-38  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-11  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-8   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-23  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-32  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-17  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-1   0.535  0.538  0.555  0.616  0.631  0.657  0.671  0.683  0.726  0.741
tr-31  0.240  0.242  0.255  0.305  0.318  0.342  0.356  0.367  0.412  0.430
tr-16  0.080  0.081  0.087  0.110  0.116  0.128  0.135  0.140  0.165  0.175
       tr-29  tr-24   tr-9  tr-15  tr-44  tr-45  tr-41   tr-2  tr-26  tr-14
tr-35 70.968 71.970 72.215 72.960 73.298 73.833 74.183 74.455 74.697 75.558
tr-20 70.333 71.335 71.580 72.325 72.663 73.198 73.548 73.820 74.063 74.923
tr-5  68.153 69.155 69.400 70.145 70.483 71.017 71.368 71.640 71.882 72.743
tr-19 51.878 52.880 53.125 53.870 54.208 54.743 55.093 55.365 55.608 56.468
tr-4  50.787 51.790 52.035 52.780 53.117 53.652 54.002 54.275 54.517 55.377
tr-34 50.225 51.228 51.473 52.217 52.555 53.090 53.440 53.713 53.955 54.815
tr-22 22.713 23.715 23.960 24.705 25.043 25.578 25.928 26.200 26.443 27.303
tr-7  15.682 16.685 16.930 17.675 18.012 18.547 18.897 19.170 19.412 20.272
tr-37 14.395 15.398 15.643 16.387 16.725 17.260 17.610 17.883 18.125 18.985
tr-28 11.470 12.473 12.718 13.462 13.800 14.335 14.685 14.958 15.200 16.060
tr-12  9.806 10.808 11.053 11.798 12.136 12.671 13.021 13.293 13.536 14.396
tr-43  9.403 10.405 10.650 11.395 11.733 12.267 12.618 12.890 13.132 13.993
tr-13  9.305 10.308 10.553 11.298 11.635 12.170 12.520 12.793 13.035 13.895
tr-33  8.697  9.700  9.945 10.690 11.027 11.562 11.912 12.185 12.427 13.287
tr-42  6.568  7.570  7.815  8.560  8.898  9.433  9.783 10.055 10.297 11.158
tr-18  6.063  7.065  7.310  8.055  8.393  8.928  9.278  9.550  9.793 10.653
tr-27  5.123  6.125  6.370  7.115  7.453  7.988  8.338  8.610  8.852  9.713
tr-39  4.623  5.625  5.870  6.615  6.953  7.488  7.838  8.110  8.352  9.213
tr-25  4.213  5.215  5.460  6.205  6.543  7.078  7.428  7.700  7.942  8.803
tr-30  2.598  3.600  3.845  4.590  4.928  5.463  5.813  6.085  6.327  7.188
tr-10  2.005  3.007  3.253  3.997  4.335  4.870  5.220  5.493  5.735  6.595
tr-29  0.000  1.002  1.248  1.992  2.330  2.865  3.215  3.488  3.730  4.590
tr-24  1.000  0.000  0.245  0.990  1.327  1.862  2.212  2.485  2.727  3.588
tr-9   1.000  1.000  0.000  0.745  1.082  1.617  1.967  2.240  2.482  3.342
tr-15  1.000  1.000  1.000  0.000  0.338  0.873  1.223  1.495  1.738  2.598
tr-44  1.000  1.000  1.000  1.000  0.000  0.535  0.885  1.158  1.400  2.260
tr-45  1.000  1.000  1.000  1.000  1.000  0.000  0.350  0.623  0.865  1.725
tr-41  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.273  0.515  1.375
tr-2   1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.242  1.102
tr-26  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.860
tr-14  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000
tr-21  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-36  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-3   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-6   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-40  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-38  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-11  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-8   1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-23  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-32  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-17  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000
tr-1   0.791  0.813  0.819  0.835  0.841  0.852  0.859  0.935  0.868  0.884
tr-31  0.490  0.521  0.528  0.552  0.562  0.579  0.590  0.766  0.606  0.632
tr-16  0.212  0.232  0.237  0.254  0.261  0.273  0.282  0.468  0.294  0.315
       tr-21  tr-36   tr-3   tr-6  tr-40  tr-38  tr-11   tr-8  tr-23   tr-32
tr-35 76.102 78.420 79.808 79.848 80.598 81.817 82.035 82.122 82.353 105.408
tr-20 75.468 77.785 79.173 79.213 79.963 81.183 81.400 81.488 81.718 104.773
tr-5  73.287 75.605 76.993 77.033 77.783 79.002 79.220 79.307 79.538 102.593
tr-19 57.013 59.330 60.718 60.758 61.508 62.728 62.945 63.033 63.263  86.318
tr-4  55.922 58.240 59.628 59.667 60.417 61.637 61.855 61.942 62.172  85.227
tr-34 55.360 57.677 59.066 59.105 59.855 61.075 61.292 61.380 61.610  84.665
tr-22 27.848 30.165 31.553 31.593 32.343 33.563 33.780 33.868 34.098  57.153
tr-7  20.817 23.135 24.523 24.563 25.312 26.532 26.750 26.837 27.068  50.123
tr-37 19.530 21.847 23.236 23.275 24.025 25.245 25.462 25.550 25.780  48.835
tr-28 16.605 18.923 20.311 20.350 21.100 22.320 22.537 22.625 22.855  45.910
tr-12 14.941 17.258 18.647 18.686 19.436 20.656 20.873 20.961 21.191  44.246
tr-43 14.537 16.855 18.243 18.283 19.033 20.252 20.470 20.557 20.788  43.843
tr-13 14.440 16.758 18.146 18.185 18.935 20.155 20.373 20.460 20.690  43.745
tr-33 13.832 16.150 17.538 17.578 18.327 19.547 19.765 19.852 20.083  43.138
tr-42 11.702 14.020 15.408 15.448 16.198 17.417 17.635 17.722 17.953  41.008
tr-18 11.198 13.515 14.903 14.943 15.693 16.913 17.130 17.218 17.448  40.503
tr-27 10.257 12.575 13.963 14.003 14.753 15.973 16.190 16.277 16.508  39.563
tr-39  9.757 12.075 13.463 13.503 14.253 15.473 15.690 15.777 16.008  39.063
tr-25  9.348 11.665 13.053 13.093 13.843 15.063 15.280 15.368 15.598  38.653
tr-30  7.733 10.050 11.438 11.478 12.228 13.448 13.665 13.752 13.983  37.038
tr-10  7.140  9.457 10.846 10.885 11.635 12.855 13.072 13.160 13.390  36.445
tr-29  5.135  7.452  8.841  8.880  9.630 10.850 11.067 11.155 11.385  34.440
tr-24  4.132  6.450  7.838  7.878  8.627  9.847 10.065 10.152 10.383  33.438
tr-9   3.887  6.205  7.593  7.633  8.382  9.602  9.820  9.907 10.138  33.192
tr-15  3.143  5.460  6.848  6.888  7.638  8.858  9.075  9.163  9.393  32.448
tr-44  2.805  5.122  6.511  6.550  7.300  8.520  8.737  8.825  9.055  32.110
tr-45  2.270  4.587  5.976  6.015  6.765  7.985  8.202  8.290  8.520  31.575
tr-41  1.920  4.237  5.626  5.665  6.415  7.635  7.852  7.940  8.170  31.225
tr-2   1.647  3.965  5.353  5.392  6.142  7.362  7.580  7.667  7.897  30.952
tr-26  1.405  3.723  5.111  5.150  5.900  7.120  7.337  7.425  7.655  30.710
tr-14  0.545  2.862  4.251  4.290  5.040  6.260  6.477  6.565  6.795  29.850
tr-21  0.000  2.317  3.706  3.745  4.495  5.715  5.932  6.020  6.250  29.305
tr-36  1.000  0.000  1.388  1.428  2.178  3.398  3.615  3.702  3.933  26.988
tr-3   1.000  1.000  0.000  0.039  0.789  2.009  2.227  2.314  2.544  25.599
tr-6   1.000  1.000  1.000  0.000  0.750  1.970  2.187  2.275  2.505  25.560
tr-40  1.000  1.000  1.000  1.000  0.000  1.220  1.437  1.525  1.755  24.810
tr-38  1.000  1.000  1.000  1.000  1.000  0.000  0.217  0.305  0.535  23.590
tr-11  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.088  0.318  23.373
tr-8   1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000  0.230  23.285
tr-23  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  0.000  23.055
tr-32  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000   0.000
tr-17  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000   1.000
tr-1   0.893  0.926  0.976  0.942  0.950  0.961  0.986  0.963  0.965   1.000
tr-31  0.649  0.717  0.879  0.757  0.777  0.808  0.914  0.815  0.820   1.000
tr-16  0.329  0.392  0.621  0.433  0.456  0.493  0.683  0.502  0.509   0.983
        tr-17    tr-1   tr-31   tr-16
tr-35 105.512 147.298 151.795 162.553
tr-20 104.877 146.663 151.160 161.918
tr-5  102.697 144.483 148.980 159.738
tr-19  86.422 128.208 132.705 143.463
tr-4   85.332 127.118 131.615 142.373
tr-34  84.770 126.556 131.052 141.810
tr-22  57.257  99.043 103.540 114.298
tr-7   50.227  92.013  96.510 107.268
tr-37  48.940  90.726  95.222 105.980
tr-28  46.015  87.801  92.297 103.055
tr-12  44.351  86.137  90.633 101.391
tr-43  43.947  85.733  90.230 100.988
tr-13  43.850  85.636  90.133 100.890
tr-33  43.242  85.028  89.525 100.283
tr-42  41.112  82.898  87.395  98.153
tr-18  40.608  82.393  86.890  97.648
tr-27  39.667  81.453  85.950  96.708
tr-39  39.167  80.953  85.450  96.208
tr-25  38.757  80.543  85.040  95.798
tr-30  37.142  78.928  83.425  94.183
tr-10  36.550  78.336  82.832  93.590
tr-29  34.545  76.331  80.827  91.585
tr-24  33.542  75.328  79.825  90.583
tr-9   33.297  75.083  79.580  90.338
tr-15  32.552  74.338  78.835  89.593
tr-44  32.215  74.001  78.497  89.255
tr-45  31.680  73.466  77.962  88.720
tr-41  31.330  73.116  77.612  88.370
tr-2   31.057  72.843  77.340  88.097
tr-26  30.815  72.601  77.097  87.855
tr-14  29.955  71.741  76.237  86.995
tr-21  29.410  71.196  75.692  86.450
tr-36  27.092  68.878  73.375  84.133
tr-3   25.704  67.490  71.987  82.744
tr-6   25.665  67.451  71.947  82.705
tr-40  24.915  66.701  71.197  81.955
tr-38  23.695  65.481  69.977  80.735
tr-11  23.477  65.263  69.760  80.518
tr-8   23.390  65.176  69.672  80.430
tr-23  23.160  64.946  69.442  80.200
tr-32   0.105  41.891  46.387  57.145
tr-17   0.000  41.786  46.283  57.040
tr-1    1.000   0.000   4.497  15.254
tr-31   1.000   1.000   0.000  10.758
tr-16   0.984   1.000   1.000   0.000
Goups of means at sig.level = 0.05 
      Means G1
p0/n1  2.57  a
p0/n0  2.30  a

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
      p0/n1 p0/n0
p0/n1 0.000 0.268
p0/n0 0.323 0.000
Goups of means at sig.level = 0.05 
         Means G1
p1/n1/k1  3.16  a
p1/n1/k0  2.80  a

Matrix of the difference of means above diagonal and
respective p-values of the Tukey test below diagonal values
         p1/n1/k1 p1/n1/k0
p1/n1/k1     0.00    0.367
p1/n1/k0     0.36    0.000

TukeyC documentation built on May 2, 2019, 8:50 a.m.