This function is aimed to provide a summary suitable for unreplicated/fractional designs.
table2kunrep(object)fitted model of class aov or lm.
a data.frame containing the estimated effects, the sum of squares (SS), the sum o squares percentual contribution (SSPC), the effects' relative difference with respect to the overal mean (PRD).
library(planex)
data(semicondutores1rep)
semicondutores1rep <- treatcomb2factors(semicondutores1rep)
fit <- lm(rendimento ~ A*B*C*D*E, data = semicondutores1rep)
table2kunrep(fit)
#> effects SS SSPC PRD
#> A 11.8125 1116.28125 9.57 38.69
#> B 33.9375 9214.03125 79.00 111.16
#> C 9.6875 750.78125 6.44 31.73
#> D -0.8125 5.28125 0.05 -2.66
#> E 0.4375 1.53125 0.01 1.43
#> A:B 7.9375 504.03125 4.32 26.00
#> A:C 0.4375 1.53125 0.01 1.43
#> B:C 0.0625 0.03125 0.00 0.20
#> A:D -0.0625 0.03125 0.00 -0.20
#> B:D -0.6875 3.78125 0.03 -2.25
#> C:D 0.8125 5.28125 0.05 2.66
#> A:E 0.9375 7.03125 0.06 3.07
#> B:E 0.5625 2.53125 0.02 1.84
#> C:E 0.3125 0.78125 0.01 1.02
#> D:E -1.1875 11.28125 0.10 -3.89
#> A:B:C -0.4375 1.53125 0.01 -1.43
#> A:B:D 0.3125 0.78125 0.01 1.02
#> A:C:D -0.4375 1.53125 0.01 -1.43
#> B:C:D 0.4375 1.53125 0.01 1.43
#> A:B:E -0.1875 0.28125 0.00 -0.61
#> A:C:E 0.3125 0.78125 0.01 1.02
#> B:C:E 0.9375 7.03125 0.06 3.07
#> A:D:E 0.8125 5.28125 0.05 2.66
#> B:D:E 0.1875 0.28125 0.00 0.61
#> C:D:E -0.8125 5.28125 0.05 -2.66
#> A:B:C:D -0.0625 0.03125 0.00 -0.20
#> A:B:C:E 0.1875 0.28125 0.00 0.61
#> A:B:D:E 0.9375 7.03125 0.06 3.07
#> A:C:D:E -0.3125 0.78125 0.01 -1.02
#> B:C:D:E -0.9375 7.03125 0.06 -3.07
#> A:B:C:D:E -0.1875 0.28125 0.00 -0.61