size_b.three_way: Three-way analysis of variance - nested and mixed...

In OPDOE: Optimal Design of Experiments

Description

Returns the optimal number of levels for factor B.

Usage

size_b.three_way_mixed_ab_in_c.model_3_a(alpha, beta, delta, a, c, n, cases)

Arguments

alpha	Risk of 1st kind
beta	Risk of 2nd kind
delta	The minimum difference to be detected
a	Number of levels of fixed factor A
c	Number of levels of fixed factor C
n	Number of replications
cases	Specifies whether the "maximin" or "maximin" sizes are to be determined

Details

see chapter 3 in the referenced book

Value

Integer giving the size.

Note

Better use size.anova which allows a cleaner notation.

Author(s)

Dieter Rasch, Juergen Pilz, L.R. Verdooren, Albrecht Gebhardt, Minghui Wang

References

Dieter Rasch, Juergen Pilz, L.R. Verdooren, Albrecht Gebhardt: Optimal Experimental Design with R, Chapman and Hall/CRC, 2011

See Also

size.anova

Examples

size_b.three_way_mixed_ab_in_c.model_3_a(0.05, 0.1, 0.5, 6, 5, 1, "maximin")
size_b.three_way_mixed_ab_in_c.model_3_a(0.05, 0.1, 0.5, 6, 5, 1, "minimin")
size_b.three_way_mixed_cxbina.model_4_a(0.05, 0.1, 0.5, 6, 4, 1, "maximin")
size_b.three_way_mixed_cxbina.model_4_a(0.05, 0.1, 0.5, 6, 4, 1, "minimin")
size_b.three_way_mixed_cxbina.model_4_c(0.05, 0.1, 0.5, 6, 4, 1, "maximin")
size_b.three_way_mixed_cxbina.model_4_c(0.05, 0.1, 0.5, 6, 4, 1, "minimin")
size_b.three_way_mixed_cxbina.model_4_axc(0.05, 0.1, 0.5, 6, 4, 1, "maximin")
size_b.three_way_mixed_cxbina.model_4_axc(0.05, 0.1, 0.5, 6, 4, 1, "minimin")
size_b.three_way_nested.model_6_a(0.05, 0.1, 0.5, 6, 4, 2, "maximin")
size_b.three_way_nested.model_6_a(0.05, 0.1, 0.5, 6, 4, 2, "minimin")

OPDOE documentation built on May 1, 2019, 8:45 p.m.