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264 reglog 2020 #266

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b5d38a3
protótipo de código para simplificar output simpático dos modelos
philsf Nov 4, 2019
da0996a
código aplicado ao último modelo glm
philsf Nov 4, 2019
aab6ff7
OR/IC do teste de Fisher (obs: diferença numérica 2o dígito no IC)
philsf Nov 4, 2019
c64baae
Não carregar o script RLM no GLM (ggplots podem ser lentos)
philsf Nov 4, 2019
d93db29
código de output para modelos RLM
philsf Nov 4, 2019
3eb48a4
frame de conclusão da seção RLM - todos os modelos juntos
philsf Nov 4, 2019
7e24aa0
typo (sinal negativo)
philsf Nov 18, 2019
f2dc276
Merge tag 'v2019.2-INTO' into 264-reglog-2020
philsf Nov 20, 2019
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24 changes: 24 additions & 0 deletions Aulas/BE-Regressao-Logistica-cap31-32.tex
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Original file line number Diff line number Diff line change
Expand Up @@ -695,6 +695,30 @@ \subsection{Regressão Linear Múltipla}
\end{exampleblock}
\end{frame}

\begin{frame}{\scriptsize Conclusão}
\begin{center}
Qual das quatro estimativas de BMI é a melhor?

\bigskip
Por que?
\end{center}
\end{frame}

\begin{frame}{\scriptsize Qual das estimativas é melhor? Por que?}
\begin{exampleblock}{\scriptsize Modelo 1 -- BMI (estimativa ``crua'')}
-1.99, IC: [-2.40, -1.59]
\end{exampleblock}
\begin{exampleblock}{\scriptsize Modelo 2.1 -- BMI ajustado por idade}
-2.04, IC: [-2.37, -1.70]
\end{exampleblock}
\begin{exampleblock}{\scriptsize Modelo 2.2 -- BMI ajustado por vitamina D sérica}
-1.91, IC: [-2.14, -1.68]
\end{exampleblock}
\begin{exampleblock}{\scriptsize Modelo 3 -- BMI ajustado por idade + vitamina D sérica}
-1.95, IC: [-2.05, -1.85]
\end{exampleblock}
\end{frame}

\section{Regressão Logística}

\subsection{Regressão Logística}
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15 changes: 9 additions & 6 deletions Aulas/Cap31-32/glm.R
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Expand Up @@ -2,26 +2,29 @@ library(philsfmisc)

# dados simulados ---------------------------------------------------------

source('~/Documents/Docencia/Bioestatistica/Aulas/Cap31-32/rlm.R')
dados.rlm <- fread("Aulas/Cap31-32/dados-rlm.csv", stringsAsFactors = TRUE)
dados.rlm$vitD <- factor(dados.rlm$vitD, levels = c("baixa", "media", "alta"))
dados.rlm$osteo <- relevel(dados.rlm$osteo, "Sadio")
summary(dados.rlm)

# modelos -----------------------------------------------------------------

glm.modelo4 <- glm(osteo ~ idoso, binomial, dados.rlm)
summary(glm.modelo4)

c(format.float(exp(coef(glm.modelo4)[2])), format.interval(exp(confint.default(glm.modelo4)[2, ])))
paste0("OR: ", format.float(exp(coef(glm.modelo4)[2])), ", IC: ", format.interval(exp(confint.default(glm.modelo4)[2, ])))

tc.idoso.osteo <- with(dados.rlm, table(idoso, osteo))
fisher.test(tc.idoso.osteo)
paste0("OR: ", format.float(fisher.test(tc.idoso.osteo)$estimate), ", IC: ", format.interval(fisher.test(tc.idoso.osteo)$conf.int))

glm.modelo5 <- glm(osteo ~ BMI + idade + vitD, binomial, dados.rlm)
summary(glm.modelo5)

c(format.float(exp(coef(glm.modelo5)[2])), format.interval(exp(confint.default(glm.modelo5)[2, ])))
c(format.float(exp(coef(glm.modelo5)[3])), format.interval(exp(confint.default(glm.modelo5)[3, ])))
c(format.float(exp(coef(glm.modelo5)[4])), format.interval(exp(confint.default(glm.modelo5)[4, ])))
c(format.float(exp(coef(glm.modelo5)[5])), format.interval(exp(confint.default(glm.modelo5)[5, ])))
paste0("OR: ", format.float(exp(coef(glm.modelo5)[2])), ", IC: ", format.interval(exp(confint.default(glm.modelo5)[2, ])))
paste0("OR: ", format.float(exp(coef(glm.modelo5)[3])), ", IC: ", format.interval(exp(confint.default(glm.modelo5)[3, ])))
paste0("OR: ", format.float(exp(coef(glm.modelo5)[4]), 7), ", IC: ", format.interval(exp(confint.default(glm.modelo5)[4, ]), 7))
paste0("OR: ", format.float(exp(coef(glm.modelo5)[5]), 7), ", IC: ", format.interval(exp(confint.default(glm.modelo5)[5, ]), 7))

# graficos ----------------------------------------------------------------

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4 changes: 4 additions & 0 deletions Aulas/Cap31-32/rlm.R
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Expand Up @@ -17,10 +17,14 @@ rlm.modelo2.2 <- lm(BMD ~ BMI + vitD, data = dados.rlm)
rlm.modelo3 <- lm(BMD ~ BMI + idade + vitD, data = dados.rlm)

print(summary(rlm.modelo1))
paste0(format.float(coef(rlm.modelo1)[2]), ", IC: ", format.interval(confint.default(rlm.modelo1)[2, ]))
print(summary(rlm.modelo2))
print(summary(rlm.modelo2.1))
paste0(format.float(coef(rlm.modelo2.1)[2]), ", IC: ", format.interval(confint.default(rlm.modelo2.1)[2, ]))
print(summary(rlm.modelo2.2))
paste0(format.float(coef(rlm.modelo2.2)[2]), ", IC: ", format.interval(confint.default(rlm.modelo2.2)[2, ]))
print(summary(rlm.modelo3))
paste0(format.float(coef(rlm.modelo3)[2]), ", IC: ", format.interval(confint.default(rlm.modelo3)[2, ]))

# graficos ----------------------------------------------------------------

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