ips-universitaria/clase11_diplomado.Rmd at master · Teett/ips-universitaria · GitHub

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---
title: "clase_11_diplomado"
author: "Luis Daniel Chavarría"
date: "6/3/2020"
output: html_document
editor_options:
  chunk_output_type: console
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## Librerías

```{r}
library(tidyverse)
library(lubridate)
library(plotly)
library(broom)
```

# Lectura de datos

```{r}
diplomado <- read_csv2("database/clean_diplomate.csv") %>%
  filter(!(estotal == "SD" | estotal == "N/A")) %>%
  mutate(estb1 = as.numeric(estb1),
         estb3 = as.numeric(estb3),
         estotal = as.numeric(estotal),
         estuce = as.numeric(estuce),
         estuci = as.numeric(estuci),
         atencion = as.character(atencion),
         id = as.character(id),
         edad = as.numeric(edad),
         genero = as_factor(genero),
         cronico = as_factor(cronico),
         segcronico = as_factor(segcronico),
         eps = as_factor(eps),
         espinter = as_factor(espinter),
         urg = as_factor(urg),
         tipurg = as_factor(tipurg),
         inter = as_factor(inter),
         ordurg = as_factor(ordurg),
         cirugia = as_factor(cirugia),
         proc = as_factor(proc),
         pisodes = as_factor(pisodes),
         esp = as_factor(esp),
         anoing = as_date(anoing),
         mesing = as.character(mesing),
         diaing = as.character(diaing)
         )
```

# Ajuste de regresión lineal

```{r}
glimpse(diplomado)

age_fit <- lm(estotal ~ edad, data = diplomado)

tidy(age_fit)
glance(age_fit)
```

# Predicción

```{r}
datos_nuevos <- tibble(edad = c(23, 35))
predict(age_fit, newdata = datos_nuevos)
```

# Reto

```{r}
cronicos_piso2 <- diplomado %>%
  filter(cronico == "Sí", pisodes == "Piso 2", genero == "Masculino")

modelo_cronicos <- lm(estotal ~ estb3, data = cronicos_piso2)

modelo_cronicos %>%
  tidy()

modelo_cronicos %>%
  glance()

ggplot(cronicos_piso2, aes(x = estb3, y = estotal)) +
  geom_point() +
  geom_smooth(method = "lm")

cor(cronicos_piso2$estotal, modelo_cronicos$fitted.values)
```

```{r}
summary(lm(estotal ~ estb1*estb3*cronico, data = diplomado))
```