LRcontrast-package: Dose Response Signal Detection under Model Uncertainty

In LRcontrast: Dose Response Signal Detection under Model Uncertainty

Description

Provides functions for calculating test statistics, simulating quantiles and simulating p-values of likelihood ratio contrast tests in regression models with a lack of identifiability.

Details

Package:	LRcontrast
Type:	Package
Version:	1.0
Date:	2015-06-21
License:	GPL-3

The main functions are:
qLRcontrast: Simulates quantiles of likelihood ratio contrast tests
sLRcontrast: Calculates test statistics of likelihood ratio contrast tests
pLRcontrast: Simulates p-values of likelihood ratio contrast tests

Author(s)

Kevin Kokot

Maintainer: Kevin Kokot <[e-mail]>

References

Dette, H., Titoff, S., Volgushev, S. and Bretz, F. (2015), Dose response signal detection under model uncertainty. Biometrics. doi: 10.1111/biom.12357

See Also

DoseFinding

Examples

# Simulate the 90%, 95% and 99% quantiles of the LR contrast tests where the specified 
# models are competing against each other.
# The size of each dose group is equal in this case.

qLRcontrast(dose = c(0, 0.05, 0.2, 0.6, 1), probs = c(0.9, 0.95, 0.99), weight 
            = c(0.2, 0.2, 0.2, 0.2, 0.2), models = c("linear", "emax", 
            "exponential", "linlog"), nsim = 10)

# Calculate the LR test statistics with the same underlying models.
# In this case the data is generated by the constant model, i.e. the 
# null hypothesis of no dose response is true.

resp <- rnorm(n = 50, mean = 0.2)
dose <- c(rep(0, 10), rep(0.05, 10), rep(0.2, 10), rep(0.6, 10), rep(1, 10))

sLRcontrast(dose = dose, resp = resp, models = c("linear", "emax", "exponential", "linlog"))
			 
# Calculate the p-values in this scenario
			 
pLRcontrast(dose = dose, resp = resp, models = c("linear", "emax", "exponential", "linlog"), 
            nsim = 10)

Example output

% done    	 nsim done	 secs passed	 secs remaining ~
10 		 1 		 0 		 20 		 2 		 0 		 30 		 3 		 0 		 40 		 4 		 0 		 50 		 5 		 0 		 60 		 6 		 0 		 70 		 7 		 0 		 80 		 8 		 0 		 90 		 9 		 0 		 100 		 10 		 0 		 0
                 0.9     0.95     0.99
linear      1.346930 1.445917 1.525106
emax        1.699900 2.499869 3.139843
exponential 1.306897 1.439765 1.546059
linlog      1.297674 1.935674 2.446074
max         1.745353 2.522595 3.144389
            statistic
linear         0.6806
emax           1.0345
exponential    0.6081
linlog         0.8798
max            1.0345
% done    	 nsim done	 secs passed	 secs remaining ~
10 		 1 		 0 		 020 		 2 		 0 		 030 		 3 		 0 		 040 		 4 		 0 		 050 		 5 		 0 		 060 		 6 		 0 		 070 		 7 		 0 		 080 		 8 		 0 		 090 		 9 		 0 		 0100 		 10 		 0 		 0
            unadj-p adj-p
linear          0.0   0.3
emax            0.1   0.1
exponential     0.2   0.3
linlog          0.1   0.2

LRcontrast documentation built on May 2, 2019, 5:10 a.m.