Risk.display {epicalc} | R Documentation |
Display of various epidemiological modelling results in a medically understandable format
logistic.display(logistic.model, alpha = 0.05, decimal = 3) idr.display(count.model, decimal = 3, alpha = 0.05) mlogit.display(multinom.model, decimal = 2, alpha = 0.05) ordinal.or.display(ordinal.model, decimal = 3, alpha = 0.05)
logistic.model |
a model from a logistic regression |
alpha |
significance level |
decimal |
number of decimal places displayed |
count.model |
a model from a Poisson or negative binomial regression |
multinom.model |
a model from multinomial or polytomous regression |
ordinal.model |
a model from an ordinal logistic regression |
R provides several epidemiological modelling techniques. The functions above display these results in a format easier for medical people to understand.
Virasakdi Chongsuvivatwong <cvirasak@medicine.psu.ac.th>
'glm', 'confint'
model0 <- glm(case ~ induced + spontaneous, family=binomial, data=infert) summary(model0) logistic.display(model0) library(MASS) library(nnet) # Ordinal logistic regression options(contrasts = c("contr.treatment", "contr.poly")) house.plr <- polr(Sat ~ Infl + Type + Cont, weights = Freq, data = housing) house.plr ordinal.or.display(house.plr) # Polytomous or multinomial logistic regression house.multinom <- multinom(Sat ~ Infl + Type + Cont, weights = Freq, data = housing) summary(house.multinom) mlogit.display(house.multinom, alpha=.01) # with 99 percent confidence limits.