Aliases: recovery
Keywords: datasets
### ** Examples ### set up one-way ANOVA amod <- aov(minutes ~ blanket, data = recovery) ### set up multiple comparisons: one-sided Dunnett contrasts rht <- glht(amod, linfct = mcp(blanket = "Dunnett"), alternative = "less") ### cf. Westfall et al. (1999, p. 80) confint(rht, level = 0.9)
Simultaneous Confidence Intervals
Multiple Comparisons of Means: Dunnett Contrasts
Fit: aov(formula = minutes ~ blanket, data = recovery)
Quantile = 1.8428
90% family-wise confidence level
Linear Hypotheses:
Estimate lwr upr
b1 - b0 >= 0 -2.13333 -Inf 0.82210
b2 - b0 >= 0 -7.46667 -Inf -4.51123
b3 - b0 >= 0 -1.66667 -Inf -0.03622
### the same rht <- glht(amod, linfct = mcp(blanket = c("b1 - b0 >= 0", "b2 - b0 >= 0", "b3 - b0 >= 0"))) confint(rht, level = 0.9)
Simultaneous Confidence Intervals
Multiple Comparisons of Means: User-defined Contrasts
Fit: aov(formula = minutes ~ blanket, data = recovery)
Quantile = 1.843
90% family-wise confidence level
Linear Hypotheses:
Estimate lwr upr
b1 - b0 >= 0 -2.13333 -Inf 0.82241
b2 - b0 >= 0 -7.46667 -Inf -4.51093
b3 - b0 >= 0 -1.66667 -Inf -0.03605