summary.elrm(elrm) | R Documentation |
Summary method for class elrm
that formats and prints out the results of an elrm
object.
## S3 method for class 'elrm': summary(object, ...)
object |
an object of class elrm , resulting from a call to elrm() or a previous call to update() . |
... |
additional arguments to the summary function (currently unused). |
The following results are formatted and printed to the screen: the matched call, coefficient estimates and confidence intervals for each model term of interest, estimated p-value for jointly testing that the parameters of interest are simultaneously equal to zero, full conditional p-values from separately testing each parameter equal to zero, length of the Markov chain that inference was based on, and the Monte Carlo standard error of each reported p-value.
David Zamar, Jinko Graham, Brad McNeney
Zamar David. Monte Carlo Markov Chain Exact Inference for Binomial Regression Models. Master's thesis, Statistics and Actuarial Sciences, Simon Fraser University, 2006.
Zamar D, McNeney B and Graham J. elrm: Software Implementing Exact-like Inference for Logistic Regression Models. Journal of Statistical Software 2007, 21(3).
# Drug dataset example with both sex and treatment as the variables of interest data(drugDat); drug.elrm=elrm(formula=recovered/n~sex+treatment,interest=~sex+treatment,r=4,iter=100000,burnIn=1000,dataset=drugDat); # Summarize the results: summary(drug.elrm); # Call: # [[1]] # elrm(formula = recovered/n ~ sex + treatment, interest = ~sex + # treatment, r = 4, iter = 1e+05, dataset = drugDat, burnIn = 1000) # Results: # estimate p-value p-value_se mc_size # joint NA 0.12951 0.00216 99000 # sex 0.29479 0.54092 0.00880 2749 # treatment 0.82389 0.06892 0.00347 13131 # 95% Confidence Intervals for Parameters # lower upper # sex -0.6109481 1.209525 # treatment -0.1042183 2.028083 ## Not run: # Urinary tract dataset example with dia as the variable of interst data(utiDat); uti.elrm=elrm(uti/n~age+current+dia+oc+pastyr+vi+vic+vicl+vis,interest=~dia,r=4,iter=30000,burnIn=1000,dataset=utiDat); # Summarize the results: summary(uti.elrm); # Call: # [[1]] # elrm(formula = uti/n ~ age + current + dia + oc + pastyr + vi + # vic + vicl + vis, interest = ~dia, r = 4, iter = 30000, dataset = uti, # burnIn = 1000) # Results: # estimate p-value p-value_se mc_size # dia 2.07146 0.03286 0.00802 29000 # 95% Confidence Intervals for Parameters # lower upper # dia -0.06231932 Inf ## End(Not run)