Fahrmeir (version 2016.5.31)

cells: Cellular Differentiation

Description

The effect of two agents of immuno-activating ability that may induce cell differentiation was investigated.

Usage

data(cells)

Arguments

Format

A data frame with 16 observations on the following 3 variables.
y
number of cells differentiating
TNF
dose of TNF, U/ml
IFN
dose of IFN, U/ml

Source

Ludwig Fahrmeir, Gerhard Tutz (1994): Multivariate Statistical Modelling Based on Generalized Linear Models. Springer Series in Statistics. Springer Verlag. New-York Berlin Heidelberg

Details

The effect of two agents of immuno-activating ability that may induce cell differentiation was investigated. As response variable the number of cells that exhibited markers after exposure was recorded. It is of interest if the agents TNF (tumor necrosis factor) and IFN (interferon) stimulate cell differentiation independently, or if there is a synergetic effect. 200 cells were examined at each dose combination.

Examples

str(cells)
cells.poisson <- glm(y~TNF+IFN+TNF:IFN, data=cells, 
                    family=poisson)
summary(cells.poisson)
confint(cells.poisson)
# Now we follow the book, example 2.6, page 51:
# there seems to be overdispersion?
cells.quasi <- glm(y~TNF+IFN+TNF:IFN, data=cells, 
                    family=quasipoisson)
summary(cells.quasi)
anova(cells.quasi)
confint(cells.quasi)
# We follow the book, example 2.7, page 56:
with(cells, tapply(y, factor(TNF), function(x) c(mean(x), var(x))))
# which might indicate the use of a negative binomial model