[R] Aid on two-way ANOVA with contrasts

[joseclaudio.faria]

Dears members of R list,

It would like that a more experienced statician in R helped me to complete
the analysis to follow:

r = gl(3, 8, label = c('r1', 'r2', 'r3'))
e = rep(gl(2, 4, label = c('e1', 'e2')), 3)
y = c(26.2, 26.0, 25.0, 25.4, 24.8, 24.6, 26.7, 25.2, 25.7, 26.3, 25.1, 26.4,
         19.6, 21.1, 19.0, 18.6, 22.8, 19.4, 18.8, 19.2, 19.8, 21.4, 22.8, 21.3)

df = data.frame(r, e, y)
attach(df)
  par(mfrow=c(2,1))
  interaction.plot(r, e, y, col = 'blue', ylab = 'y', xlab = 'r')

  interaction.plot(e, r, y, col = 'blue', ylab = 'y', xlab = 'r')
  av1 = aov(y ~ r*e)

  av2 = aov(y ~ r/e)
  efR_E = summary(av2, split = list('r:e' = list('e1 vs e2/r1' = 1, 'e1 vs
e2/r2' = 2, 'e1 vs e2/r3' = 3)))

  av3  = aov(y ~ e/r)
  efE_R = summary(av3, split = list('e:r' = list('r/e1' = c(1,3), 'r/e2' =
c(2,4))))

  mds = model.tables(av1, ty = 'means')
detach(df)

cat('\nData:'); cat('\n')
print(df)

cat('\nMeans:'); cat('\n')
print(mds)

cat('\nANOVA:'); cat('\n')
print(summary(av1)); cat('\n')

cat('\nANOVA - E effect in R levels:'); cat('\n')
print(efR_E); cat('\n')

cat('\nANOVA - R effect in E levels:'); cat('\n')
print(efE_R); cat('\n')

#I would like to get as resulted (efE_R) like this:
# ANOVA - R effect (contrasts) in E levels:
#                                    Df       Sum Sq    Mean Sq   F value
Pr(>F)
# e                                  1     19.082
#  e:r                            (4)  (156.622)
#    e:r: r/e1                 (2)     (87.122)
#      r1 vs (r2,r3)/e1     1      ?...
#      r2 vs r3/e1            1      ?
#    e:r: r/e2                  (2)   (69.500)
#      r1 vs (r2,r3)/e1      1      ?...
#      r2 vs r3/e2             1      ?...
# Residuals                  18   23.090     1.283



#Through manual calculations I got:
# ANOVA - R effect in E levels:
#                                Df       Sum Sq    Mean Sq   F value    Pr(>F)
# e                              1         19.082
#  e:r                        (4)      (156.622)
#    e:r: r/e1             (2)         (87.122)
#      r1 vs (r2,r3)/e   1           19.26
#      r2 vs r3/e1        1           67.86
#    e:r: r/e2             (2)         (69.500)
#      r1 vs (r2,r3)/e   1           63.38
#      r2 vs r3/e2        1             6.12
# Residuals            18          23.090     1.283

Best regards,

José Cláudio Faria
UESC/DCET
Brasil
73-634.2779
joseclaudio.faria at terra.com.br
jc_faria at uol.com.br