##################################################################### # NAME: Chris Bilder # # DATE: 3-8-12 # # PURPOSE: Use a Poisson regression model with Larry Bird data # # # # NOTES: # ##################################################################### #Create contingency table - notice the data is entered by columns c.table<-array(data = c(251, 48, 34, 5), dim = c(2,2), dimnames = list(First = c("made", "missed"), Second = c("made", "missed"))) bird<-as.data.frame(as.table(c.table)) bird mod.fit1<-glm(formula = Freq ~ First + Second, data = bird, family = poisson(link = log)) summary(mod.fit1) mod.fit2<-glm(formula = Freq ~ First + Second + First:Second, data = bird, family = poisson(link = log)) summary(mod.fit2) #Estimates of mu predict(object = mod.fit1, newdata = bird, type = "response") Pearson.test<-chisq.test(x = c.table, correct = FALSE) Pearson.test$expected predict(object = mod.fit2, newdata = bird, type = "response") bird$Freq #LRT for interaction library(package = car) Anova(mod.fit2, test = "LR") anova(mod.fit1, mod.fit2, test = "Chisq") library(package = vcd) assocstats(c.table) #Using a multinomial regression model instead - because there are only two categories # the function may not be working as it should??? library(package = nnet) mod.fit3<-multinom(formula = Second ~ First, weight = Freq, data = bird) summary(mod.fit3) Anova(mod.fit3) #Does not work mod.fit4<-multinom(formula = Second ~ 1, weight = Freq, data = bird) summary(mod.fit4) anova(mod.fit4, mod.fit3) #-2log(Lambda) same as before #Logistic regression bird<-data.frame(First = c(0,1), success = c(251, 48), trials = c(285, 53)) bird mod.fit<-glm(formula = success/trials ~ First, weight = trials, family = binomial(link = logit), data = bird) summary(mod.fit) Anova(mod.fit, test = "LR") #-2log(Lambda) same as before #