Transforms a signed root deviance profile to a modified likelihood root profile.

hoa(object, maxstat = 10)

Arguments

object

An object of class mcprofile

maxstat

Limits the statistic to a maximum absolute value (default=10)

Value

An object of class mcprofile with a hoa profile in the srdp slot.

See also

mcprofile

Examples

####################################### ## cell transformation assay example ## ####################################### str(cta)
#> 'data.frame': 80 obs. of 2 variables: #> $ conc: num 0 0 0 0 0 0 0 0 0 0 ... #> $ foci: int 0 1 0 0 0 0 0 0 0 2 ...
## change class of cta$conc into factor cta$concf <- factor(cta$conc, levels=unique(cta$conc)) ggplot(cta, aes(y=foci, x=concf)) + geom_boxplot() + geom_dotplot(binaxis = "y", stackdir = "center", binwidth = 0.2) + xlab("concentration")
# glm fit assuming a Poisson distribution for foci counts # parameter estimation on the log link # removing the intercept fm <- glm(foci ~ concf-1, data=cta, family=poisson(link="log")) ### Comparing each dose to the control by Dunnett-type comparisons # Constructing contrast matrix library(multcomp) CM <- contrMat(table(cta$concf), type="Dunnett") # calculating signed root deviance profiles (dmcp <- mcprofile(fm, CM))
#> #> Multiple Contrast Profiles #> #> Estimate Std.err #> 0.01 - 0 0.511 0.730 #> 0.03 - 0 -0.405 0.913 #> 0.1 - 0 1.386 0.645 #> 0.3 - 0 2.159 0.610 #> 1 - 0 2.730 0.596 #> 3 - 0 2.813 0.594 #> 10 - 0 2.979 0.592 #>
# computing profiles for the modified likelihood root hp <- hoa(dmcp) plot(hp)
# comparing confidence intervals confint(hp)
#> #> mcprofile - Confidence Intervals #> #> level: 0.95 #> adjustment: single-step #> #> Estimate lower upper #> 0.01 - 0 0.511 -1.2533 2.50 #> 0.03 - 0 -0.405 -2.9578 1.86 #> 0.1 - 0 1.386 -0.0427 3.23 #> 0.3 - 0 2.159 0.8658 3.94 #> 1 - 0 2.730 1.4878 4.49 #> 3 - 0 2.813 1.5766 4.57 #> 10 - 0 2.979 1.7516 4.73 #>
confint(dmcp)
#> #> mcprofile - Confidence Intervals #> #> level: 0.95 #> adjustment: single-step #> #> Estimate lower upper #> 0.01 - 0 0.511 -1.2484 2.55 #> 0.03 - 0 -0.405 -3.0509 1.87 #> 0.1 - 0 1.386 -0.0169 3.31 #> 0.3 - 0 2.159 0.8964 4.03 #> 1 - 0 2.730 1.5197 4.59 #> 3 - 0 2.813 1.6086 4.67 #> 10 - 0 2.979 1.7838 4.83 #>