Nothing
# 1. Prepare data
library(erer); data(daIns)
daInsH <- daIns[, -14] # with HuntYrs
daInsF <- daIns[, -3] # with FishYrs
fm.hunt <- Y ~ Injury + HuntYrs + Nonres + Lspman + Lnong +
Gender + Age + Race + Marital + Edu + Inc + TownPop
fm.hunt2 <- bsFormu(name.y = "Y", name.x = colnames(daIns)[-c(1, 14)])
lg <- binomial(link = "logit")
# 2. Run regressions
HA <- glm(formula = Y ~ Injury + HuntYrs + Nonres + Lspman + Lnong +
Gender + Age + Race + Marital + Edu + Inc + TownPop,
family = binomial(link = "logit"), data = daIns, x = TRUE)
HB <- glm(family = lg, data = daIns, x = TRUE, formula = fm.hunt)
HC <- glm(family = lg, data = daInsH, x = TRUE, formula = Y ~ .)
HD <- glm(family = lg, data = daInsH, x = TRUE, formula = formula(daInsH))
HE <- glm(family = lg, data = daIns, x = TRUE, formula = formula(daInsH))
FA <- glm(family = lg, data = daInsF, x = TRUE, formula = formula(daInsF))
FB <- update(object = HA, formula = formula(daInsF))
# 3. Understand outputs
class(HA)
head(x = methods(class = "glm"), n = 4)
names(HA); names(summary(HA))
(aic.value <- summary(HA)$aic)
# 4. Extract selected outputs
HH <- summary(HA)$coefficients; head(HH)
FF <- summary(FA)$coefficients
ta <- bsTab(w = HH, need = "2T")
tb <- bsTab(w = FF, need = "2T")
ab <- merge(x = ta, y = tb, by = "Variable", all = TRUE, sort = FALSE)
out <- ab[c(1, 2, 13, 14, 3:12), ]
out[1, 1] <- "Constant"
colnames(out) <- c("Variable", "A_estimate", "A_t.ratio",
"B_estimate", "B_t.ratio")
out[is.na(out)] <- "___"; out
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.