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---
title: "Events and missing data report"
author: "Produced by the Clinical Research Facility - Cork"
date: "`r Sys.Date()`"
output: pdf_document
includes:
      in_header: \usepackage{color}
keep_tex: true
---

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 correlationL <- list()
  i           <- 1
  
  for (r in seq(.75, .95, .05)){     # Correlations
    
    for (n in seq(10, 1000, 10)){    # Sample sizes
      
      z      <- atanh(r)             # Fisher's transformation
      sez    <- 1 / sqrt(n - 3)      # SE of transformed variable
      lower  <- z - (1.96 * sez)

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library(gmodels)
library(vcd)
library(magrittr)

# This Works

table(factor(sample(c("Aa", "Ab"), 500, replace = T)),
      factor(sample(c("Ba", "Bb"), 500, replace = T)),
      dnn = c("A", "B")) %>%
{

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\documentclass{article}
\usepackage{booktabs} 
\usepackage{caption} 
\usepackage{array} 
\usepackage{float}
\usepackage[cm]{fullpage}

\begin{document}
\begin{tabular}{p{3.0cm}ccccc} 
\toprule

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Sex & 3 &  &   &   &  \\
\multicolumn{1}{r}{Male} &   & 51\%  & 50\%  & 60\% \\
\multicolumn{1}{r}{Female} &   & 49\%  & 50\%  & 40\% \\
Gestational Age (wks) & 0 & 40.3(39.3 to 41)  & 40.3(39.3 to 41)  & 40.1(39.4 to 41) \\
Birth weight (g) & 3 & 3460(3150 to 3770)  & 3430(3120 to 3720)  & 4390(4065 to 4605) \\
Birth length (cm) & 71 & 50.2(49 to 51.8)  & 50(48.9 to 51.5)  & 53(51.5 to 54) \\
Fat mass (\%) & 531 & 10.9(8.2 to 13.8)  & 10.6(8 to 13.4)  & 16(13.1 to 18.5) \\
Age (yrs) & 0 & 30(28 to 33)  & 30(28 to 33)  & 31(28 to 33) \\
Height (cm) & 0 & 165(161 to 168)  & 165(161 to 168)  & 165(160.2 to 169) \\
Weight (kg) & 0 & 65(59.2 to 74)  & 65(60 to 74)  & 65(58 to 75.8) \\

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  summaryA <- function(data, ...){

    # Example
    #
    # data <- data.frame("A" = rnorm(500, 0, 1),
    #                    "B" = rnorm(500, 0, 1),
    #                    "C" = factor(sample(c("Ca", "Cb"), 500, replace = T)))
    #
    # a <- summaryA(data)
    #

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  require(plyr)
  require(ggplot2)
  require(RColorBrewer)
  
  Df <- data.frame(Method = replicate(100,sample(c("A","B","C", "D", "E"),1)),
                   Year   = sample(c(1980:2014), 100, replace = T))
  Df$count <- 1
  
  Df <- Df[order(Df[,2]), ] # Sort by year