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<body>
<title >
Introducción al muestreo complejo en R
</title><div id="wrap"><div class="container"><div class="row row-offcanvas row-offcanvas-right"><div class="contents col-xs-12 col-md-10">
<h1 id="tutorial-de-muestreo-en-r">Tutorial de muestreo en R</h1>
<p><strong>Fecha: octubre 19, 2014</strong></p>
<p><strong>Por Felipe Jiménez</strong></p>
<h2 id="introducción">Introducción</h2>
<p>El presente tutorial tiene como objetivo principal el introducir al usuario en el muestreo simple y complejo en el ambiente de programación analítica R.Se cubren los siguientes temas:</p>
<ul>
<li>La selección de tamaños de muestra simples(<code>base</code> y <code>dplyr</code>),<br /></li>
<li>selección sistemática y cálculo de tamaños de muestra(<code>SamplinUtil</code>),<br /></li>
<li>cálculo de intervalos de confianza(<code>DescTools</code>),<br /></li>
<li>selección de muestras con PPT (<code>pps</code>),<br /></li>
<li>Muestreo complejo con el paquete <code>survey</code>.<br /></li>
<li>Comparación de los resultados arrojados en R con información oficial de la Encuesta de Hogares del INEC.</li>
</ul>
<h2 id="configuración-de-r-y-rstudio">Configuración de R y Rstudio</h2>
<p>El primer paso para iniciar con el tutorial es instalar <a href="http://cran.rstudio.com/">la consola de R</a>(En el triste caso de aún no contar con él).</p>
<p>Posteriormente, es altamente recomendado utilizar el IDE <a href="http://www.rstudio.com/products/rstudio/download/">Rstudio</a>, para una mayor facilidad en el desarrollo de las aplicaciones.</p>
<p>Una vez con la instalación de nuestras dos herramientas, procedemos a crear un nuevo documento <a href="http://rmarkdown.rstudio.com/">Rmarkdown</a> Y escogemos las opciones por defecto, como se ilustra en la siguiente figura:</p>
<p><embed src="https://www.dropbox.com/s/aes3xp4xs2zrpx7/Captura1.png?dl=1" /></p>
<p>Una vez abierto el nuevo documento R markdown, guardarlo y a continuación borrar el código que trae por defecto como ejemplo, a excepción del encabezado encerrado con tres slash (<code>---</code>) al inicio del documento.</p>
<hr />
<h2 id="ejercicios">Ejercicios</h2>
<h3 id="selección-de-muestras-simples">Selección de muestras simples</h3>
<p><strong>Muestreo irrestricto Aleatorio<a href="http://www.virtual.unal.edu.co/cursos/sedes/manizales/4030006/lecciones/capituloseis/6_5.html">(MIA)</a></strong>:</p>
<p>El R Base contiene la útil función <code>sample</code> en la que se pueden obtener muestras aleatorias con o sin reemplazo de manera sencilla.</p>
<p>Vamos a cargar un dataset para ejemplificar y a cuantificar sus dimensiones:</p>
<div class="row"><button class="source R toggle btn btn-xs btn-primary">
<span class="glyphicon glyphicon-chevron-down"></span> R source
</button><pre style=""><code class="source r">crime<-data.frame(crimtab)
dim(crime)</code></pre><button class="output R toggle btn btn-xs btn-success">
<span class="glyphicon glyphicon-chevron-down"></span> R output
</button><pre style=""><code class="output r">## [1] 924 3
</code></pre></div>
<p>Como podemos ver, el dataset <code>crime</code> contiene 924 filas y 3 columnas.Seguidamente seleccionamos una muestra de 30 casos sin reemplazo:</p>
<div class="row"><button class="source R toggle btn btn-xs btn-primary">
<span class="glyphicon glyphicon-chevron-down"></span> R source
</button><pre style=""><code class="source r">#Selección de la muestra
#Tamaño de la muestra
n<-30
muestramia<- sample(1:nrow(crime),n,replace=FALSE)
muestramia</code></pre><button class="output R toggle btn btn-xs btn-success">
<span class="glyphicon glyphicon-chevron-down"></span> R output
</button><pre style=""><code class="output r">## [1] 457 172 763 616 731 100 665 378 752 593 716 505 484 720 22 434 918
## [18] 629 433 780 397 222 64 90 285 467 595 365 818 263
</code></pre><button class="source R toggle btn btn-xs btn-primary">
<span class="glyphicon glyphicon-chevron-down"></span> R source
</button><pre style=""><code class="source r">#Asignar los elementos de la muestra al data frame de datos
crimemuestramia<- crime[muestramia, ]
head(crimemuestramia)</code></pre><button class="output R toggle btn btn-xs btn-success">
<span class="glyphicon glyphicon-chevron-down"></span> R output
</button><pre style=""><code class="output r">## Var1 Var2 Freq
## 457 13 167.64 3
## 172 9.7 152.4 0
## 763 10 187.96 0
## 616 12.1 177.8 10
## 731 11 185.42 0
## 100 10.9 147.32 0
</code></pre></div>
<h4 id="selección-de-muestras-simples-con-dplyr">Selección de muestras simples con <code>dplyr</code></h4>
<p>Una forma más sencilla de obtener una muestra es con el paquete <code>dplyr</code>.Este paquete es sumamente útil para el tratamiento de datos, adicionalmente contiene una función para obtener muestras simples de un data frame:</p>
<div class="row"><button class="source R toggle btn btn-xs btn-primary">
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</button><pre style=""><code class="source r">library(dplyr)
#Muestra sin reemplazo
crimemuestramia2<- crime %.%
sample_n(size=n,replace=FALSE)
head(crimemuestramia2)</code></pre><button class="output R toggle btn btn-xs btn-success">
<span class="glyphicon glyphicon-chevron-down"></span> R output
</button><pre style=""><code class="output r">## Var1 Var2 Freq
## 308 10.7 160.02 16
## 601 10.6 177.8 0
## 238 12.1 154.94 0
## 441 11.4 167.64 26
## 706 12.7 182.88 2
## 78 12.9 144.78 0
</code></pre><button class="source R toggle btn btn-xs btn-primary">
<span class="glyphicon glyphicon-chevron-down"></span> R source
</button><pre style=""><code class="source r">#Muestra con pesos
crimemuestramia3<- crime %.%
sample_n(size=n,weight=Freq)
head(crimemuestramia3)</code></pre><button class="output R toggle btn btn-xs btn-success">
<span class="glyphicon glyphicon-chevron-down"></span> R output
</button><pre style=""><code class="output r">## Var1 Var2 Freq
## 225 10.8 154.94 6
## 272 11.3 157.48 10
## 572 11.9 175.26 10
## 440 11.3 167.64 26
## 352 10.9 162.56 27
## 276 11.7 157.48 9
</code></pre><button class="source R toggle btn btn-xs btn-primary">
<span class="glyphicon glyphicon-chevron-down"></span> R source
</button><pre style=""><code class="source r">#Muestra con una proporción de casos
crimemuestramia4<- crime %.%
sample_frac(0.05)
head(crimemuestramia4);dim(crimemuestramia4)</code></pre><button class="output R toggle btn btn-xs btn-success">
<span class="glyphicon glyphicon-chevron-down"></span> R output
</button><pre style=""><code class="output r">## Var1 Var2 Freq
## 161 12.8 149.86 0
## 697 11.8 182.88 0
## 419 13.4 165.1 0
## 471 10.2 170.18 0
## 191 11.6 152.4 2
## 211 9.4 154.94 0
</code></pre><button class="output R toggle btn btn-xs btn-success">
<span class="glyphicon glyphicon-chevron-down"></span> R output
</button><pre style=""><code class="output r">## [1] 46 3
</code></pre></div>
<hr />
<h3 id="selección-de-muestras-sistemáticasinstalación-del-paquete-samplingutils">Selección de muestras sistemáticas(Instalación del paquete <code>SamplingUtils</code>)</h3>
<p>Para el ejemplo del muestreo sistemático utilizaremos la función <code>sys.sample</code> del paquete <code>SamplingUtil</code>.Para instalar este paquete, se debe inicialmente instalar el paquete <code>devtools</code> ya que no se encuentra en CRAN.Las instrucciones son las siguientes:</p>
<p><strong>Instalar devtools:</strong><code>install.packages("devtools")</code><br /><strong>Cargar libreria:</strong> <code>library(devtools)</code></p>
<p><strong>Instalar SamplingUtils:</strong><code>install_github("DFJL/SamplingUtils")</code></p>
<p>De esta manera podemos proceder a generar la muestra sistemática:</p>
<div class="row"><button class="source R toggle btn btn-xs btn-primary">
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</button><pre style=""><code class="source r">#Cargar libreria:
library(SamplingUtil)
muestrasis<- sys.sample(nrow(crime),30)
muestrasis</code></pre><button class="output R toggle btn btn-xs btn-success">
<span class="glyphicon glyphicon-chevron-down"></span> R output
</button><pre style=""><code class="output r">## [1] 11 41 71 101 131 161 191 221 251 281 311 341 371 401 431 461 491
## [18] 521 551 581 611 641 671 701 731 761 791 821 851 881
</code></pre><button class="source R toggle btn btn-xs btn-primary">