Teste_de_Fisher_e_Razao_de_Chances.R

# https://stats.oarc.ucla.edu/other/mult-pkg/faq/general/faq-how-do-i-interpret-odds-ratios-in-logistic-regression/
dados = matrix(c(74, 17, 77, 32), ncol = 2)
dados
dimnames(dados) <- list(voto = c("Normal","Menção Honrosa"),
                        sexo = c("Masculino","Feminino"))
dados

mosaicplot(dados, color = c("skyblue", "pink"), xlab ="Menção Honrosa",
           ylab = "Sexo")

prob_m = 17/(17+74+32+77)
prob_f = 32/(17+74+32+77)

odds_m =  17/74
odds_f =  32/77

odds_f/odds_m

fisher.test(dados)

#------------------------------------------------------------------------------------------------
dados = matrix(c(69, 13, 33, 2), ncol = 2)
dimnames(dados) <- list(sexo = c("Feminino", "Masculino"),
                         voto = c("Kelmon","Não Kelmon"))
dados

mosaicplot(dados, color = c("darkred", "gold"), xlab ="Sexo",
           ylab = "Voto no candidato padre")
aa = chisq.test(dados)
aa$expected
fisher.test(dados)

# sample odds-ratio estimate
69*2/(13*33)
a = 69/33
b = 13/2
a/b
b/a

#------------------------------------------------------------------------------------------------
load(url("https://github.com/DATAUNIRIO/Base_de_dados/raw/refs/heads/master/Titanic.RData"))

tabela <- table(Titanic$Sexo, Titanic$Sobreviveu)
tabela

mosaicplot(tabela, color = c("darkred", "gold"), xlab ="Sexo", ylab = "Survivência")

TF <- fisher.test(tabela)
TF

TF
cf = 344/126
cf
cm = 366/1364
cm

cf/cm
cm/cf

# This shows that the odds ratio is about 10—the odds of a female surviving were about ten times the odds of a male surviving. 
# This is (female survival / female death) / (male survival / male death). 
# The order of the values in the odds ratios is determined by the order of the values of each variable;by default R uses alphabetical order.
# https://whitlockschluter3e.zoology.ubc.ca/RLabs/R_tutorial_Contingency_analysis.html#odds_ratios


#Titanic$vivo = ifelse(Titanic$Sobreviveu=="Sobreviveu",1,0)
#Titanic$aaa = ifelse(Titanic$Sexo=="Masculino",0,1)
#modelo = glm(vivo ~ aaa, data = Titanic)
#summary(modelo)
#exp(0.52035)
# razao de chances condicionais 68% maior de sobreviver

#--------------------------------------------------------------
### Tabela para o teste
Tabela <- as.table(rbind(c(2,3,10,6,1), c(1,6,7,14,12)))

### Rótulos para tabela
dimnames(Tabela) <- list(sexo = c("Feminino", "Masculino"),
                         likert = c("Concordo Totalmente","Concordo",
                                    "Nem concordo nem discordo",
                                    "Discordo", "Discordo Totalmente"))
Tabela


Teste_fisher_hybrid <- fisher.test(Tabela,  hybrid=TRUE)
Teste_fisher_hybrid