hoa: Higher order asymptotics using the modified likelihood root In mcprofile: Testing Generalized Linear Hypotheses for Generalized Linear Model Parameters by Profile Deviance

Description

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

Usage

 `1` ```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.

Author(s)

Daniel Gerhard

`mcprofile`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34``` ```####################################### ## cell transformation assay example ## ####################################### str(cta) ## 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)) # computing profiles for the modified likelihood root hp <- hoa(dmcp) plot(hp) # comparing confidence intervals confint(hp) confint(dmcp) ```