anova like function

anova 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))

# S3 method for class 'glmerMod'
anovax(object, ..., test = "x2", control = list(nsim = 1000, cl = NULL))

# S3 method for class 'gls'
anovax(object, ..., test = "x2", control = list(nsim = 1000, cl = NULL))

# S3 method for class 'lm'
anovax(object, ..., test = "x2", control = list(nsim = 1000, cl = NULL))

# S3 method for class 'anovax'
print(x, ...)

Arguments

object

A model object object

...

further arguments

test

A character string

control

A list controling simulations, only relevant for parametric bootstrapping.

x

anovax object

Author

Søren Højsgaard

Examples

fm1 <- lmer(sugpct ~ block + sow + harvest + (1|block:harvest), data=beets)
fm0 <- update(fm1, .~. - sow)
#> boundary (singular) fit: see help('isSingular')
anovax(fm1, .~. - harvest, test="KR")
#>           stat    df   ddf p.value
#> KR_Ftest 15.21  1.00  2.00  0.0599
anovax(fm1, .~. - harvest, test="SAT")
#>            stat    df   ddf p.value
#> SAT_Ftest 15.21  1.00  2.00  0.0599
anovax(fm1, .~. - harvest, test="PB", control=list(nsim=50, cl=1))
#>          stat df ddf p.value
#> PBtest 11.815 NA  NA  0.0784

anovax(fm1, test="KR")
#> boundary (singular) fit: see help('isSingular')
#> boundary (singular) fit: see help('isSingular')
#>              stat        df       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(fm1, test="SAT")
#> boundary (singular) fit: see help('isSingular')
#> boundary (singular) fit: see help('isSingular')
#> boundary (singular) fit: see help('isSingular')
#>              stat        df       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(fm1, test="PB", control=list(nsim=50, cl=1))
#> boundary (singular) fit: see help('isSingular')
#> boundary (singular) fit: see help('isSingular')
#> boundary (singular) fit: see help('isSingular')
#> boundary (singular) fit: see help('isSingular')
#> boundary (singular) fit: see help('isSingular')
#>             stat df ddf p.value
#> block    0.82682 NA  NA  0.7059
#> sow     74.30490 NA  NA  0.0196
#> harvest 11.81501 NA  NA  0.1177
## anovax(fm1, test="PBF", control=list(nsim=50, cl=1))