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getSummary(fit, sided=2, method=NULL)
snp.logistic
, snp.matched
, glm()
, or
a list with names "parms" and "cov" containing parameter estimates and
the variance-covariance matrix for the estimates. No default. parms
if parms
is a vector.
summary(glm.obj)$coefficients
, except
the p-values are always computed using the normal distribution.
parms <- 1:5
cov <- matrix(data=1, nrow=5, ncol=5)
getSummary(list(parms=parms, cov=cov))
# Compare to summary()
set.seed(123)
n <- 100
y <- rbinom(n, 1, 0.5)
x <- cbind(runif(n), rbinom(n, 1, 0.5))
fit <- glm(y ~ x, family=binomial())
sum <- summary(fit)
sum$coefficients
getSummary(fit)
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