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Commit b6b0a4af authored by Hugues de Courson's avatar Hugues de Courson
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module3/exo3/exercice_fr.Rmd
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...@@ -54,7 +54,8 @@ vivantes_nonfum <- sum(data$Status[data$Smoker=="No"]=="Alive") ...@@ -54,7 +54,8 @@ vivantes_nonfum <- sum(data$Status[data$Smoker=="No"]=="Alive")
decedees_fum <- sum(data$Status[data$Smoker=="Yes"]=="Dead") decedees_fum <- sum(data$Status[data$Smoker=="Yes"]=="Dead")
decedees_nonfum <- sum(data$Status[data$Smoker=="No"]=="Dead") decedees_nonfum <- sum(data$Status[data$Smoker=="No"]=="Dead")
tab_1 <- data.frame(Vivantes = c(vivantes_fum,vivantes_nonfum), Decedees = c(decedees_fum,decedees_nonfum), row.names = c("Fumeuses","Non fumeuses")) tab_1 <- data.frame(Vivantes = c(vivantes_fum,vivantes_nonfum),
Decedees = c(decedees_fum,decedees_nonfum), row.names = c("Fumeuses","Non fumeuses"))
kable(tab_1,align = 'l') kable(tab_1,align = 'l')
``` ```
...@@ -73,7 +74,10 @@ nb_viv <- sum(data$Status=="Alive") ...@@ -73,7 +74,10 @@ nb_viv <- sum(data$Status=="Alive")
nb_deces <-sum(data$Status=="Dead") nb_deces <-sum(data$Status=="Dead")
tot <- sum(data$Status=="Alive"|data$Status=="Dead") tot <- sum(data$Status=="Alive"|data$Status=="Dead")
tab_2 <- data.frame(cbind(rbind(mort_fum, vivant_fum, nb_fum)), rbind(mort_nonfum,vivant_nonfum, nb_nonfum),rbind(nb_deces,nb_viv,tot)) tab_2 <- data.frame(cbind(rbind(mort_fum, vivant_fum, nb_fum)),
rbind(mort_nonfum,vivant_nonfum, nb_nonfum),
rbind(nb_deces,nb_viv,tot))
row.names(tab_2) <- c("Decedees", "Vivantes","Total") row.names(tab_2) <- c("Decedees", "Vivantes","Total")
names(tab_2) <- c("Fumeuses", "Non Fumeuses", "Total") names(tab_2) <- c("Fumeuses", "Non Fumeuses", "Total")
...@@ -83,8 +87,10 @@ kable(tab_2,align = "c") ...@@ -83,8 +87,10 @@ kable(tab_2,align = "c")
# Representation graphique # Representation graphique
Ceci passe par la création d'un tableau avec les pourcentages de mortalité Ceci passe par la création d'un tableau avec les pourcentages de mortalité
```{r representation graphique taux de mortalite} ```{r representation graphique taux de mortalite}
tab_3 <- data.frame(cbind(rbind((sum(data$Status[data$Smoker=="Yes"]=="Dead")/sum(data$Smoker=="Yes"))*100,(sum(data$Status[data$Smoker=="Yes"]=="Alive")/sum(data$Smoker=="Yes"))*100)), tab_3 <- data.frame(cbind(rbind((sum(data$Status[data$Smoker=="Yes"]=="Dead")/sum(data$Smoker=="Yes"))*100,
rbind((sum(data$Status[data$Smoker=="No"]=="Dead")/sum(data$Smoker=="No"))*100,(sum(data$Status[data$Smoker=="No"]=="Alive")/sum(data$Smoker=="No"))*100)) (sum(data$Status[data$Smoker=="Yes"]=="Alive")/sum(data$Smoker=="Yes"))*100)),
rbind((sum(data$Status[data$Smoker=="No"]=="Dead")/sum(data$Smoker=="No"))*100,
(sum(data$Status[data$Smoker=="No"]=="Alive")/sum(data$Smoker=="No"))*100))
names(tab_3) <- c("Fumeuses", "Non fumeuses") names(tab_3) <- c("Fumeuses", "Non fumeuses")
row.names(tab_3) <- c("Decedees", "Vivantes") row.names(tab_3) <- c("Decedees", "Vivantes")
...@@ -156,10 +162,12 @@ tab_5 <- ftable(data[,c(1,2,4)]) ...@@ -156,10 +162,12 @@ tab_5 <- ftable(data[,c(1,2,4)])
tab_5 <- round(prop.table(tab_5,2)*100,1) tab_5 <- round(prop.table(tab_5,2)*100,1)
tab_5 <- rbind(tab_5, tab1(data$cl_age)$output.table[,1]) tab_5 <- rbind(tab_5, tab1(data$cl_age)$output.table[,1])
tab_5 <- as.table(tab_5) tab_5 <- as.table(tab_5)
row.names(tab_5) <- c("Non fumeuses vivantes ", "Non fumeuses decedees", "Fumeuses vivantes", "Fumeuses decedees" ,"Effectifs") row.names(tab_5) <- c("Non fumeuses vivantes ", "Non fumeuses decedees",
"Fumeuses vivantes", "Fumeuses decedees" ,"Effectifs")
colnames(tab_5) <- c("[18;34]", "[35;54]", "[55;64]", "[65;[") colnames(tab_5) <- c("[18;34]", "[35;54]", "[55;64]", "[65;[")
kable(tab_5,"latex", align = "c") %>% kable_styling(latex_options = "striped", stripe_index = c(1,2)) kable(tab_5,"latex", align = "c") %>% kable_styling(latex_options = "striped",
stripe_index = c(1,2))
``` ```
## Et maintenant on trace les barplots ## Et maintenant on trace les barplots
...@@ -170,14 +178,18 @@ Et autre [lien](https://sites.google.com/site/rgraphiques/realiser-des-graphique ...@@ -170,14 +178,18 @@ Et autre [lien](https://sites.google.com/site/rgraphiques/realiser-des-graphique
```{r deuxieme barplot} ```{r deuxieme barplot}
par(mar = c(5,5,5,13)) par(mar = c(5,5,5,13))
barplot(tab_5[c(1:4),], col = c("gray","black","gray","black"), density = c(30,30,40,100),angle = c(70,70,0,0)) barplot(tab_5[c(1:4),], col = c("gray","black","gray","black"), density = c(30,30,40,100),
angle = c(70,70,0,0))
xmin <- par("usr")[1] xmin <- par("usr")[1]
xmax <- par("usr")[2] xmax <- par("usr")[2]
ymin <- par("usr")[3] ymin <- par("usr")[3]
ymax <- par("usr")[4] ymax <- par("usr")[4]
par(xpd=TRUE) par(xpd=TRUE)
lambda <- 0.025 lambda <- 0.025
legend(((1 + lambda) * par("usr")[2] - lambda * par("usr")[1]),50, legend = c("Non fumeuses vivantes", "Non fumeuses decedees", "Fumeuses vivantes", "Fumeuses decedees"), fill = c("gray","black","gray","black"),density = c(30,30,40,100),angle = (c(70,70,0,0))) legend(((1 + lambda) * par("usr")[2] - lambda * par("usr")[1]),50,
legend = c("Non fumeuses vivantes", "Non fumeuses decedees",
"Fumeuses vivantes", "Fumeuses decedees"),
fill = c("gray","black","gray","black"),density = c(30,30,40,100),angle = (c(70,70,0,0)))
``` ```
...@@ -199,8 +211,8 @@ On récupère les valeurs min et max du plot précédent ...@@ -199,8 +211,8 @@ On récupère les valeurs min et max du plot précédent
## Et maintenant on peut obtenir les intervalles de confiance ## Et maintenant on peut obtenir les intervalles de confiance
<!--# Pour le premier groupe d'age non fumeuses decedees--> #Pour le premier groupe d'age non fumeuses decedees
```{r IC premier groupe dage non fum, include=FALSE} ```{r IC premier groupe dage non fum}
x <- tab_5[2,1] x <- tab_5[2,1]
n <- tab_5[5,1] n <- tab_5[5,1]
...@@ -209,8 +221,8 @@ IC1<- round(IC(x),1) ...@@ -209,8 +221,8 @@ IC1<- round(IC(x),1)
IC1 <- paste(c(IC1[1],"[",IC1[2],"-",IC1[3],"]"),collapse = "") IC1 <- paste(c(IC1[1],"[",IC1[2],"-",IC1[3],"]"),collapse = "")
``` ```
<!--# Pour le premier groupe d'age fumeuses decedees--> # Pour le premier groupe d'age fumeuses decedees
```{r IC premier groupe dage fum, include=FALSE} ```{r IC premier groupe dage fum}
x <- tab_5[4,1] x <- tab_5[4,1]
n <- tab_5[5,1] n <- tab_5[5,1]
...@@ -219,8 +231,8 @@ IC2 <- round(IC(x),1) ...@@ -219,8 +231,8 @@ IC2 <- round(IC(x),1)
IC2 <- paste(c(IC2[1],"[",IC2[2],"-",IC2[3],"]"), collapse = "") IC2 <- paste(c(IC2[1],"[",IC2[2],"-",IC2[3],"]"), collapse = "")
``` ```
<!--# Pour le deuxième groupe d'age non fum--> # Pour le deuxième groupe d'age non fum
```{r IC deuxieme groupe dage non fum, include=FALSE} ```{r IC deuxieme groupe dage non fum}
x <- tab_5[2,2] x <- tab_5[2,2]
n <- tab_5[5,2] n <- tab_5[5,2]
...@@ -229,8 +241,8 @@ IC3 <- round(IC(x),1) ...@@ -229,8 +241,8 @@ IC3 <- round(IC(x),1)
IC3 <- paste(c(IC3[1],"[",IC3[2],"-",IC3[3],"]"),collapse = "") IC3 <- paste(c(IC3[1],"[",IC3[2],"-",IC3[3],"]"),collapse = "")
``` ```
<!--# Pour le deuxième groupe d'age fum--> # Pour le deuxième groupe d'age fum
```{r IC deuxieme groupe dage fum, include=FALSE} ```{r IC deuxieme groupe dage fum}
x <- tab_5[4,2] x <- tab_5[4,2]
n <- tab_5[5,2] n <- tab_5[5,2]
...@@ -239,8 +251,8 @@ IC4 <- round(IC(x),1) ...@@ -239,8 +251,8 @@ IC4 <- round(IC(x),1)
IC4 <- paste(c(IC4[1],"[",IC4[2],"-",IC4[3],"]"),collapse = "") IC4 <- paste(c(IC4[1],"[",IC4[2],"-",IC4[3],"]"),collapse = "")
``` ```
<!--# Pour le troisieme groupe d'age non fum--> # Pour le troisieme groupe d'age non fum
```{r IC troisieme groupe dage non fum, include=FALSE} ```{r IC troisieme groupe dage non fum}
x <- tab_5[2,3] x <- tab_5[2,3]
n <- tab_5[5,3] n <- tab_5[5,3]
...@@ -249,8 +261,8 @@ IC5 <- round(IC(x),1) ...@@ -249,8 +261,8 @@ IC5 <- round(IC(x),1)
IC5 <- paste(c(IC5[1],"[",IC5[2],"-",IC5[3],"]"),collapse = "") IC5 <- paste(c(IC5[1],"[",IC5[2],"-",IC5[3],"]"),collapse = "")
``` ```
<!--# Pour le troisieme groupe d'age fum--> # Pour le troisieme groupe d'age fum
```{r IC troisieme groupe dage fum, include=FALSE} ```{r IC troisieme groupe dage fum}
x <- tab_5[4,3] x <- tab_5[4,3]
n <- tab_5[5,3] n <- tab_5[5,3]
...@@ -258,8 +270,8 @@ n <- tab_5[5,3] ...@@ -258,8 +270,8 @@ n <- tab_5[5,3]
IC6 <- round(IC(x),1) IC6 <- round(IC(x),1)
IC6 <- paste(c(IC6[1],"[",IC6[2],"-",IC6[3],"]"),collapse = "") IC6 <- paste(c(IC6[1],"[",IC6[2],"-",IC6[3],"]"),collapse = "")
``` ```
<!--# Pour le quatrieme groupe d'age non fum--> # Pour le quatrieme groupe d'age non fum
```{r IC quatrieme groupe dage non fum, include=FALSE} ```{r IC quatrieme groupe dage non fum}
x <- tab_5[2,4] x <- tab_5[2,4]
n <- tab_5[5,4] n <- tab_5[5,4]
...@@ -269,8 +281,8 @@ IC7 <- paste(c(IC7[1],"[",IC7[2],"-",IC7[3],"]"),collapse = "") ...@@ -269,8 +281,8 @@ IC7 <- paste(c(IC7[1],"[",IC7[2],"-",IC7[3],"]"),collapse = "")
``` ```
<!--# Pour le quatrieme groupe d'age fum--> Pour le quatrieme groupe d'age fum
```{r IC quatrieme groupe dage fum, include=FALSE} ```{r IC quatrieme groupe dage fum}
x <- tab_5[4,4] x <- tab_5[4,4]
n <- tab_5[5,4] n <- tab_5[5,4]
...@@ -334,7 +346,8 @@ Pour cela on introduit un polynome fractionnaire dans le modèle de régression. ...@@ -334,7 +346,8 @@ Pour cela on introduit un polynome fractionnaire dans le modèle de régression.
library(mfp) library(mfp)
reguniage2 <- mfp(deces~fp(Age, df =4, select = 1, scale = T), family = binomial, data = data) reguniage2 <- mfp(deces~fp(Age, df =4, select = 1, scale = T),
family = binomial, data = data)
summary(reguniage2) summary(reguniage2)
``` ```
...@@ -351,4 +364,8 @@ logistic.display(regtot) ...@@ -351,4 +364,8 @@ logistic.display(regtot)
``` ```
Et là on constate une inversion de l'odds ratio associé au tabac lorsque l'on ajuste sur l'âge... Et là on constate une inversion de l'odds ratio associé au tabac lorsque l'on ajuste sur l'âge...
\ No newline at end of file Soit l'âge est un facteur confondant sur la relation entre le fait d'être fumeur et le risque de décés, soit il s'agit d'un modificateur de l'effet.
Dans tous les cas l'interprétation brute du de la relation entre le fait de fumer et l'âge n'est pas juste.
module3/exo3/exercice_fr.log
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