Description Usage Arguments Details Value Examples
poisson.test
estimates the rate parameter for one or two groups of
counts using Bayesian estimation assuming a Poisson distribution. This
procedure is intended as a replacement for prop.test
.
1 2 3  bayes.poisson.test(x, T = 1, r = 1, alternative = c("two.sided", "less",
"greater"), cred.mass = 0.95, n.iter = 15000, progress.bar = "none",
conf.level)

x 
number of events. A vector of length one or two. 
T 
time base for event count. A vector of length one or two. 
r 
hypothesized rate or rate ratio 
alternative 
ignored and is only retained in order to mantain
compatibility with 
cred.mass 
the amount of probability mass that will be contained in
reported credible intervals. This argument fills a similar role as

n.iter 
The number of iterations to run the MCMC sampling. 
progress.bar 
The type of progress bar. Possible values are "text", "gui", and "none". 
conf.level 
same as 
Give data on the number of counts x during T periods (e.g., days, hours, years, etc.) the underlying rate λ is estimated assuming the following model:
x ~ Poisson(λ·T)
λ ~ Gamma(0.5, 0.00001)
Here the Gamma prior on λ is an approximation of Jeffrey's' prior for this model. In the case of two groups, both rate parameters are separately estimated using the model above. For two groups, the ratio of the rates is calculated where a ratio of, say, 2.5 would mean that the rate of group 1 is 2.5 times that of group 2. Note that the mean and the highest desity interval for the rate ratio are calculated on the log transformed samples and then transformed back to the original scale.
A list of class bayes_one_sample_poisson_test
or
bayes_two_sample_poisson_test
that contains information about the
analysis. It can be further inspected using the functions summary
,
plot
, diagnostics
and model.code
.
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  # Data from Boice, J. D., & Monson, R. R. (1977).
# Breast cancer in women after repeated fluoroscopic examinations of the chest.
# Journal of the National Cancer Institute, 59(3), 823832.
# 41 cases of breast cancer during 28,010 personyears in the treatment group
# of women receiving Xray fluoroscopy and 15 cases of breast cancer during
# 19 017 personyears in the control group.
no_cases < c(41, 15)
no_years < c(28010, 19017)
bayes.poisson.test(no_cases, no_years)
# Save the return value in order to inspect the model result further.
fit < bayes.poisson.test(no_cases, no_years)
summary(fit)
plot(fit)
# MCMC diagnostics (should not be necessary for such a simple model)
diagnostics(fit)
# Print out the R code to run the model. This can be copy'n'pasted into
# an Rscript and further modified.
model.code(fit)

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