t1
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t1, T, T, F, F, 0.05)
Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr,  : 
  ‘lower’ not specified or contains NA
Além disso: Mensagens de aviso:
1: In .local(.Object, ...) :
  The conditional covariance matrix has zero diagonal elements
2: In cov2cor(covariance(object, partial = FALSE)) :
  diag(V) had non-positive or NA entries; the non-finite result may be dubious
> friedman.test(scores ~ diet | colony, data=waste_t1)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = NaN, df = 3, p-value = NA

t2
> friedman.test(scores ~ diet | colony, data=waste_t2)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = NaN, df = 3, p-value = NA

t3
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t3, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1.4142, p-value = 0.4904
alternative hypothesis: two.sided

t4
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t4, T, T, F, F, 0.05)
Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr,  : 
  ‘lower’ not specified or contains NA
Além disso: Mensagens de aviso:
1: In .local(.Object, ...) :
  The conditional covariance matrix has zero diagonal elements
2: In cov2cor(covariance(object, partial = FALSE)) :
  diag(V) had non-positive or NA entries; the non-finite result may be dubious
> friedman.test(scores ~ diet | colony, data=waste_t4)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = NaN, df = 3, p-value = NA

t5 
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t5, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.1909, p-value = 0.1258
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t5)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 6.6, df = 3, p-value = 0.0858

t6
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t6, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1, p-value = 0.7494
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t6)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 2, df = 3, p-value = 0.5724

t7
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t7, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.4495, p-value = 0.06844
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t7)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 6.75, df = 3, p-value = 0.08031

t8
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t8, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.1213, p-value = 0.1463
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t8)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 6, df = 3, p-value = 0.1116

t9
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t9, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1.769, p-value = 0.2884
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t9)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 3.8276, df = 3, p-value = 0.2807

t10
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t10, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 3.4641, p-value = 0.002901
alternative hypothesis: two.sided


$PostHoc.Test
                         
fruits - alt    0.0030329
gen - alt       0.0030329
leaves - alt    0.0030329
gen - fruits    1.0000000
leaves - fruits 1.0000000
leaves - gen    1.0000000

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 3.4641, p-value = 0.003051
alternative hypothesis: two.sided


$PostHoc.Test
                         
fruits - alt    0.0030329
gen - alt       0.0030329
leaves - alt    0.0030329
gen - fruits    1.0000000
leaves - fruits 1.0000000
leaves - gen    1.0000000

t11
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t11, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1.633, p-value = 0.3599
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t11)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 3.6667, df = 3, p-value = 0.2998

t12
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t12, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2, p-value = 0.1879
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t12)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 6, df = 3, p-value = 0.1116

t13
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t13, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.6458, p-value = 0.04065
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.16020552
gen - alt       1.00000000
leaves - alt    0.94188856
gen - fruits    0.16020552
leaves - fruits 0.04089334
leaves - gen    0.94188856

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.6458, p-value = 0.04085
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.16020552
gen - alt       1.00000000
leaves - alt    0.94188856
gen - fruits    0.16020552
leaves - fruits 0.04089334
leaves - gen    0.94188856

t14
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t14, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.6458, p-value = 0.04019
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.15987920
gen - alt       1.00000000
leaves - alt    0.94188787
gen - fruits    0.15987920
leaves - fruits 0.04068234
leaves - gen    0.94188787

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.6458, p-value = 0.04089
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.15987920
gen - alt       1.00000000
leaves - alt    0.94188787
gen - fruits    0.15987920
leaves - fruits 0.04068234
leaves - gen    0.94188787

t15
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t15, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.6458, p-value = 0.04075
alternative hypothesis: two.sided


$PostHoc.Test
                         
fruits - alt    0.1600387
gen - alt       1.0000000
leaves - alt    0.9418886
gen - fruits    0.1600387
leaves - fruits 0.0404968
leaves - gen    0.9418886

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.6458, p-value = 0.0413
alternative hypothesis: two.sided


$PostHoc.Test
                         
fruits - alt    0.1600387
gen - alt       1.0000000
leaves - alt    0.9418886
gen - fruits    0.1600387
leaves - fruits 0.0404968
leaves - gen    0.9418886

t16
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t16, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.6458, p-value = 0.04066
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.16004694
gen - alt       1.00000000
leaves - alt    0.94188936
gen - fruits    0.16004694
leaves - fruits 0.04108876
leaves - gen    0.94188936

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.6458, p-value = 0.04109
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.16004694
gen - alt       1.00000000
leaves - alt    0.94188936
gen - fruits    0.16004694
leaves - fruits 0.04108876
leaves - gen    0.94188936

t17
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t17, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2, p-value = 0.188
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t17)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 6, df = 3, p-value = 0.1116

t18
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t18, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1.633, p-value = 0.36
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t18)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 3.6667, df = 3, p-value = 0.2998

t19
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t19, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1.7008, p-value = 0.3231
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t19)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 4.7143, df = 3, p-value = 0.194

t20
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t20, T, T, F, F, 0.05)
Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr,  : 
  ‘lower’ not specified or contains NA
Além disso: Mensagens de aviso:
1: In .local(.Object, ...) :
  The conditional covariance matrix has zero diagonal elements
2: In cov2cor(covariance(object, partial = FALSE)) :
  diag(V) had non-positive or NA entries; the non-finite result may be dubious
> friedman.test(scores ~ diet | colony, data=waste_t20)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = NaN, df = 3, p-value = NA

t21
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t21, T, T, F, F, 0.05)
Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr,  : 
  ‘lower’ not specified or contains NA
Além disso: Mensagens de aviso:
1: In .local(.Object, ...) :
  The conditional covariance matrix has zero diagonal elements
2: In cov2cor(covariance(object, partial = FALSE)) :
  diag(V) had non-positive or NA entries; the non-finite result may be dubious
> friedman.test(scores ~ diet | colony, data=waste_t21)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = NaN, df = 3, p-value = NA

t22
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t22, T, T, F, F, 0.05)
Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr,  : 
  ‘lower’ not specified or contains NA
Além disso: Mensagens de aviso:
1: In .local(.Object, ...) :
  The conditional covariance matrix has zero diagonal elements
2: In cov2cor(covariance(object, partial = FALSE)) :
  diag(V) had non-positive or NA entries; the non-finite result may be dubious
> friedman.test(scores ~ diet | colony, data=waste_t22)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = NaN, df = 3, p-value = NA

t23
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t23, T, T, F, F, 0.05)
Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr,  : 
  ‘lower’ not specified or contains NA
Além disso: Mensagens de aviso:
1: In .local(.Object, ...) :
  The conditional covariance matrix has zero diagonal elements
2: In cov2cor(covariance(object, partial = FALSE)) :
  diag(V) had non-positive or NA entries; the non-finite result may be dubious
> friedman.test(scores ~ diet | colony, data=waste_t23)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = NaN, df = 3, p-value = NA

t24
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t24, T, T, F, F, 0.05)
Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr,  : 
  ‘lower’ not specified or contains NA
Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr,  : 
  ‘lower’ not specified or contains NA
> friedman.test(scores ~ diet | colony, data=waste_t24)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = NaN, df = 3, p-value = NA

t25
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t25, T, T, F, F, 0.05)
Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr,  : 
  ‘lower’ not specified or contains NA
Além disso: Mensagens de aviso:
1: In .local(.Object, ...) :
  The conditional covariance matrix has zero diagonal elements
2: In cov2cor(covariance(object, partial = FALSE)) :
  diag(V) had non-positive or NA entries; the non-finite result may be dubious
> friedman.test(scores ~ diet | colony, data=waste_t25)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = NaN, df = 3, p-value = NA

t26
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t26, T, T, F, F, 0.05)
Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr,  : 
  ‘lower’ not specified or contains NA
Além disso: Mensagens de aviso:
1: In .local(.Object, ...) :
  The conditional covariance matrix has zero diagonal elements
2: In cov2cor(covariance(object, partial = FALSE)) :
  diag(V) had non-positive or NA entries; the non-finite result may be dubious
> friedman.test(scores ~ diet | colony, data=waste_t26)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = NaN, df = 3, p-value = NA

t27
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t27, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.6726, p-value = 0.03732
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.37655482
gen - alt       0.70843614
leaves - alt    0.70843614
gen - fruits    0.03754539
leaves - fruits 0.95065962
leaves - gen    0.14102849

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.6726, p-value = 0.03772
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.37655482
gen - alt       0.70843614
leaves - alt    0.70843614
gen - fruits    0.03754539
leaves - fruits 0.95065962
leaves - gen    0.14102849

t28
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t28, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.0889, p-value = 0.1567
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t28)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 6.5455, df = 3, p-value = 0.08789

t29
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t29, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1.0445, p-value = 0.7232
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t29)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 1.6364, df = 3, p-value = 0.6512

t30
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t30, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1.0445, p-value = 0.7232
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t30)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 1.6364, df = 3, p-value = 0.6512

t31
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t31, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.0494, p-value = 0.1701
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t31)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 4.7143, df = 3, p-value = 0.194

t32
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t32, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1.964, p-value = 0.2017
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t32)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 4.2857, df = 3, p-value = 0.2322

t33
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t33, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1.4527, p-value = 0.4664
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t33)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 2.4419, df = 3, p-value = 0.4859

t34
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t34, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1.0809, p-value = 0.7013
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t34)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 1.4423, df = 3, p-value = 0.6956

t35
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t35, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.4019, p-value = 0.07663
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t35)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 8.3077, df = 3, p-value = 0.04006

t36
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t36, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1.7321, p-value = 0.3069
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t36)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 5.2041, df = 3, p-value = 0.1574

t37
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t37, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1.6036, p-value = 0.3765
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t37)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 3.8571, df = 3, p-value = 0.2773

t38
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t38, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.4019, p-value = 0.07654
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t38)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 6.4615, df = 3, p-value = 0.09119

t39
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t39, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.4019, p-value = 0.07672
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t39)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 6.4615, df = 3, p-value = 0.09119

t40
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t40, T, T, F, F, 0.05)
Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr,  : 
  ‘lower’ not specified or contains NA
Além disso: Mensagens de aviso:
1: In .local(.Object, ...) :
  The conditional covariance matrix has zero diagonal elements
2: In cov2cor(covariance(object, partial = FALSE)) :
  diag(V) had non-positive or NA entries; the non-finite result may be dubious
> friedman.test(scores ~ diet | colony, data=waste_t40)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = NaN, df = 3, p-value = NA

t41
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t41, T, T, F, F, 0.05)
Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr,  : 
  ‘lower’ not specified or contains NA
Além disso: Mensagens de aviso:
1: In .local(.Object, ...) :
  The conditional covariance matrix has zero diagonal elements
2: In cov2cor(covariance(object, partial = FALSE)) :
  diag(V) had non-positive or NA entries; the non-finite result may be dubious
> friedman.test(scores ~ diet | colony, data=waste_t41)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = NaN, df = 3, p-value = NA

t42
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t42, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.7175, p-value = 0.03328
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.03341042
gen - alt       0.90497193
leaves - alt    1.00000000
gen - fruits    0.17413449
leaves - fruits 0.03341042
leaves - gen    0.90497193

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.7175, p-value = 0.03303
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.03341042
gen - alt       0.90497193
leaves - alt    1.00000000
gen - fruits    0.17413449
leaves - fruits 0.03341042
leaves - gen    0.90497193

t43
friedman.test.with.post.hoc(scores ~ diet | colony, waste_t43, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 3.153, p-value = 0.008564
alternative hypothesis: two.sided


$PostHoc.Test
                           
fruits - alt    0.027478006
gen - alt       0.983538579
leaves - alt    0.766470154
gen - fruits    0.008760667
leaves - fruits 0.264291519
leaves - gen    0.541195893

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 3.153, p-value = 0.009088
alternative hypothesis: two.sided


$PostHoc.Test
                           
fruits - alt    0.027478006
gen - alt       0.983538579
leaves - alt    0.766470154
gen - fruits    0.008760667
leaves - fruits 0.264291519
leaves - gen    0.541195893

t44
friedman.test.with.post.hoc(scores ~ diet | colony, waste_t44, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.8284, p-value = 0.02417
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.14643267
gen - alt       0.89432447
leaves - alt    0.49036781
gen - fruits    0.02408973
leaves - fruits 0.89432447
leaves - gen    0.14643267

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.8284, p-value = 0.02399
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.14643267
gen - alt       0.89432447
leaves - alt    0.49036781
gen - fruits    0.02408973
leaves - fruits 0.89432447
leaves - gen    0.14643267

t45
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t45, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 3.0089, p-value = 0.01357
alternative hypothesis: two.sided


$PostHoc.Test
                         
fruits - alt    0.1585470
gen - alt       0.7910146
leaves - alt    0.6538682
gen - fruits    0.0138978
leaves - fruits 0.7910146
leaves - gen    0.1585470

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 3.0089, p-value = 0.01371
alternative hypothesis: two.sided


$PostHoc.Test
                         
fruits - alt    0.1585470
gen - alt       0.7910146
leaves - alt    0.6538682
gen - fruits    0.0138978
leaves - fruits 0.7910146
leaves - gen    0.1585470

t46
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t46, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.5927, p-value = 0.04692
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.49037160
gen - alt       0.71351049
leaves - alt    0.41821328
gen - fruits    0.06391562
leaves - fruits 0.99941515
leaves - gen    0.04679675

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.5927, p-value = 0.04725
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.49037160
gen - alt       0.71351049
leaves - alt    0.41821328
gen - fruits    0.06391562
leaves - fruits 0.99941515
leaves - gen    0.04679675

t47
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t47, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 3.6895, p-value = 0.001426
alternative hypothesis: two.sided


$PostHoc.Test
                           
fruits - alt    0.036607415
gen - alt       0.335795988
leaves - alt    0.001328252
gen - fruits    0.745765102
leaves - fruits 0.745765102
leaves - gen    0.183274261

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 3.6895, p-value = 0.001376
alternative hypothesis: two.sided


$PostHoc.Test
                           
fruits - alt    0.036607415
gen - alt       0.335795988
leaves - alt    0.001328252
gen - fruits    0.745765102
leaves - fruits 0.745765102
leaves - gen    0.183274261

t48
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t48, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.6612, p-value = 0.03865
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.23436236
gen - alt       0.86527284
leaves - alt    0.40618078
gen - fruits    0.03874561
leaves - fruits 0.98731392
leaves - gen    0.09153861

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.6612, p-value = 0.03876
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.23436236
gen - alt       0.86527284
leaves - alt    0.40618078
gen - fruits    0.03874561
leaves - fruits 0.98731392
leaves - gen    0.09153861

t49
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t49, T, T, F, F, 0.05)
$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.7775, p-value = 0.02826
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.05315717
gen - alt       0.89928982
leaves - alt    0.02815799
gen - fruits    0.24921068
leaves - fruits 0.99563484
leaves - gen    0.15864811

$Friedman.Test

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.7775, p-value = 0.02795
alternative hypothesis: two.sided


$PostHoc.Test
                          
fruits - alt    0.05315717
gen - alt       0.89928982
leaves - alt    0.02815799
gen - fruits    0.24921068
leaves - fruits 0.99563484
leaves - gen    0.15864811

t50
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t50, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 1.3339, p-value = 0.5412
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t50)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 2.5294, df = 3, p-value = 0.47

t51
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t51, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.1032, p-value = 0.1519
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t51)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 5.6939, df = 3, p-value = 0.1275

t52
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t52, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.1213, p-value = 0.1463
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t52)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 6.5, df = 3, p-value = 0.08966

t53
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t53, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.1213, p-value = 0.1463
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t53)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 6.5, df = 3, p-value = 0.08966

t54
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t54, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.1213, p-value = 0.1463
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t54)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 6.5, df = 3, p-value = 0.08966

t55
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t55, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.2602, p-value = 0.1076
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t55)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 9.2264, df = 3, p-value = 0.02643

t56
> friedman.test.with.post.hoc(scores ~ diet | colony, waste_t56, T, T, F, F, 0.05)
[1] "The results where not significant, There is no need for a post hoc test"

	Asymptotic General Symmetry Test

data:  scores by diet (alt, fruits, gen, leaves) 
	 stratified by colony
maxT = 2.2602, p-value = 0.1076
alternative hypothesis: two.sided

> friedman.test(scores ~ diet | colony, data=waste_t56)

	Friedman rank sum test

data:  scores and diet and colony
Friedman chi-squared = 9.2264, df = 3, p-value = 0.02643