anovax.Rdanova like function
print anovax object
anovax(object, ..., test = "x2", control = list(nsim = 1000, cl = NULL))
# S3 method for class 'lmerMod'
anovax(object, ..., test = "x2", control = list(nsim = 1000, cl = NULL))
# Default S3 method
anovax(object, ..., test = "x2", control = list(nsim = 1000, cl = NULL))
# S3 method for class 'anovax'
print(x, ...)lmm1 <- lmer(sugpct ~ block + sow + harvest + (1|block:harvest), data=beets)
lmm0 <- update(lmm1, .~. - sow)
#> boundary (singular) fit: see help('isSingular')
anovax(lmm1, .~. - harvest, test="KR")
#> [1] "kr"
#> $nsim
#> [1] 1000
#>
#> $cl
#> NULL
#>
#> anovax_worker dots:
#> [[1]]
#> . ~ . - harvest
#> <environment: 0x55d4292c7350>
#>
#> stat ndf ddf p.value
#> Ftest 15.21 1.00 2.00 0.0599
anovax(lmm1, .~. - harvest, test="SAT")
#> [1] "sat"
#> $nsim
#> [1] 1000
#>
#> $cl
#> NULL
#>
#> anovax_worker dots:
#> [[1]]
#> . ~ . - harvest
#> <environment: 0x55d4292c7350>
#>
#> statistic ndf ddf p.value
#> [1,] 15.21 1.00 2.00 0.0599
## anovax(lmm1, .~. - harvest, test="PB", control=list(nsim=50, cl=1))
anovax(lmm1, test="KR")
#> [1] "kr"
#> $nsim
#> [1] 1000
#>
#> $cl
#> NULL
#>
#> anovax_worker dots:
#> list()
#> stat ndf ddf p.value
#> block 0.37725 2.00000 3.00000 0.7143
#> sow 101.00000 4.00000 20.00000 0.0000
#> harvest 15.21053 1.00000 2.00000 0.0599
anovax(lmm1, test="SAT")
#> [1] "sat"
#> $nsim
#> [1] 1000
#>
#> $cl
#> NULL
#>
#> anovax_worker dots:
#> list()
#> statistic ndf ddf p.value
#> block 0.37725 2.00000 27.00000 0.6893
#> sow 101.00000 4.00000 20.00000 0.0000
#> harvest 15.21053 1.00000 2.00000 0.0599
anovax(lmm1, test="PB", control=list(nsim=50, cl=1))
#> [1] "pb"
#> $nsim
#> [1] 50
#>
#> $cl
#> [1] 1
#>
#> anovax_worker dots:
#> list()
#> stat df p.value
#> block 0.82682 NA 0.7059
#> sow 74.86841 NA 0.0196
#> harvest 12.91424 NA 0.0784