Calculates the pooled Brown-Forsythe test.

pool_levenetest Calculates the pooled F-statistic of the Brown-Forsythe test.

pool_bftest(object, method = "D1")

Arguments

object

An object of class 'mistats' ('Multiply Imputed Statistical Analysis').

method

A character vector to choose the pooling method, 'D1' (default) or 'D2'.

Value

The (combined) F-statistic, p-value and degrees of freedom.

References

Eekhout I, van de Wiel MA, Heymans MW. Methods for significance testing of categorical covariates in logistic regression models after multiple imputation: power and applicability analysis. BMC Med Res Methodol. 2017;17(1):129.

Enders CK (2010). Applied missing data analysis. New York: The Guilford Press.

Van Buuren S. (2018). Flexible Imputation of Missing Data. 2nd Edition. Chapman & Hall/CRC Interdisciplinary Statistics. Boca Raton.

See also

with.milist, bf_test

Author

Martijn Heymans, 2021

Examples

imp_dat <- df2milist(lbpmilr, impvar="Impnr")
ra <- with(imp_dat, expr=bf_test(Pain ~ factor(Carrying)))
res <- pool_bftest(ra)
res
#>       F_value df1      df2     P(>F)       RIV
#> [1,] 1.203557   2 124.4952 0.3035923 0.1472731
#> attr(,"class")
#> [1] "mipool"