waste: Industrial Waste Data Set

In multcomp: Simultaneous Inference in General Parametric Models

Industrial Waste Data Set

Description

Industrial waste output in a manufactoring plant.

Usage

data("waste")

Format

This data frame contains the following variables

temp

temperature, a factor at three levels: low, medium, high.

envir

environment, a factor at five levels: env1 ... env5.

waste

response variable: waste output in a manufacturing plant.

Details

The data are from an experiment designed to study the effect of temperature (temp) and environment (envir) on waste output in a manufactoring plant. Two replicate measurements were taken at each temperature / environment combination.

Source

P. H. Westfall, R. D. Tobias, D. Rom, R. D. Wolfinger, Y. Hochberg (1999). Multiple Comparisons and Multiple Tests Using the SAS System. Cary, NC: SAS Institute Inc., page 177.

Examples

  ### set up two-way ANOVA with interactions
  amod <- aov(waste ~ temp * envir, data=waste)

  ### comparisons of main effects only
  K <- glht(amod, linfct = mcp(temp = "Tukey"))$linfct
  K
  glht(amod, K)

  ### comparisons of means (by averaging interaction effects)
  low <- grep("low:envi", colnames(K))
  med <- grep("medium:envi", colnames(K))
  K[1, low] <- 1 / (length(low) + 1)
  K[2, med] <- 1 / (length(low) + 1)
  K[3, med] <- 1 / (length(low) + 1)
  K[3, low] <- - 1 / (length(low) + 1)
  K
  confint(glht(amod, K))

  ### same as TukeyHSD
  TukeyHSD(amod, "temp")

  ### set up linear hypotheses for all-pairs of both factors
  wht <- glht(amod, linfct = mcp(temp = "Tukey", envir = "Tukey"))

  ### cf. Westfall et al. (1999, page 181)
  summary(wht, test = adjusted("Shaffer"))

multcomp documentation built on Sept. 11, 2024, 8:06 p.m.