Description Usage Arguments Value References Examples
This function performs classical frequentist statistical inference to a discrete multivariate canonical exponential family. It produces the maximum likelihood estimator, one and twosided pvalues for the test that model parameters are zero, and providing confidence intervals for the parameters. The discrete probability model is given by a set of possible values of the random vectors, and null weights for these vectors. Such a discrete probability model arises in logistic regression, and this function is envisioned to be applied to the results of a network algorithm for conditional logistic regression. Examples apply this to data from \insertCitemehtapatel;textualPHInfiniteEstimates, citing \insertCitegoorinetal87;textualPHInfiniteEstimates.
1 
out 
List of the sort provided by network.

alpha 
Test level, or 1 confidence level. 
rng 
Range of possible parameter values. 
List with components:
ospv Observed onesided p values
tspv Observed twosided p value.
ci confidence interval.
mle Maximum likelihood estimator.
mehtapatelPHInfiniteEstimates
\insertRefgoorinetal87PHInfiniteEstimates
1 2 3 4 5 6 7 8 9 10 11  #Columns in table are:
# Lymphocytic Infiltration (1=low, 0=high)
# Sex (1=male, 0=female)
# Any Ostioid Pathology (1=yes, 0=no)
# Number in LISexAOP group
# Number in LISexAOP group with disease free interval greater than 3 y
goorin<data.frame(LI=c(0,0,0,0,1,1,1,1),Sex=c(0,0,1,1,0,0,1,1),
AOP=c(0,1,0,1,0,1,0,1),N=c(3,2,4,1,5,5,9,17),Y=c(3,2,4,1,5,3,5,6))
out<network(goorin[,1:3],goorin[,4],conditionon=1:3,resp=goorin[,5])
inference(out)

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.