ernestguevarra

library(shiny)

# WARNING: This sketch does not make proper use of the "state" parameter.
# Doing so usually involves using cookies, which can be done with the
# Rook package but I have not done that here. If you choose to use this
# approach in production, please check the state parameter properly!

APP_URL <- if (interactive()) {
  # This might be useful for local development. If not, just hardcode APP_URL
  # to the deployed URL that you'll provide a few lines below.

ernestguevarra

#
# Close graphic devices and clear the workspace
#
graphics.off()
rm(list = ls())
gc()

#
# Simulation parameters
#

ernestguevarra

################################################################################
#
#  Function to calculate z-scores for WHZ, HAZ, WAZ using the WHO Growth
#  Reference (2006) using data and methods from ISBN ISBN 92 4 154693 X.
#
################################################################################
#
#  Parameters are :
#
#    sexObserved : Sex

ernestguevarra

dist: trusty   # Use Ubuntu 14.04 image (instead of 12.04)
language: r
sudo: false
r: 3.4.1

# Install packrat if needed and have it restore packages.
install:
  - R -e 'if (system.file(package="packrat") == "") install.packages("packrat")'
  - R -e "packrat::packify(); packrat::restore()"

ernestguevarra

// Declare variables
numeric aNumber;

// Create logic variables for each of the HAZ flags
numeric hazLowerBoys;
hazLowerBoys = 0.000000379386 * cage ^ 5 - 0.000069515524 * cage ^ 4 
               + 0.004909805 * cage ^ 3 - 0.168908042 * cage ^ 2 
               + 3.266127182 * cage + 39.95107423

numeric hazUpperBoys;

ernestguevarra

Stepped wedge study design

We used the sample size calculations for a stepped wedge design proposed by Woertman et al¹. Their calculations use the unadjusted sample size ($ n_{unadjusted} $) required for an individual randomised controlled trial for comparing two proportions and then adjusts this calculation based on the cluster design effect ($ DEFF $) to be expected in a stepped wedge design. Their equation for estimating the design effect of a stepped wedge study is as follows:  

$$ DEFF_{\text {stepped wedge}} = \frac {1 + p(ktn + bn - 1)}{1 + p \left(\frac {1}{2}ktn + bn - 1 \right )} \times \frac {3(1-p)}{2t \left (k-\frac{1}{k} \right )} $$

where

$ k = \text {number of steps} $ $ b = \text {number of baseline measurements} $

ernestguevarra

<a id="FIG1"></a><strong>Figure 1:</strong> Schematic diagram of the proposed stepped wedge cluster-randomised controlled trial
<style>
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  text-align:center;
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ernestguevarra

library(dplyr)
library(sp)
library(rgdal)
library(tibble)

find_UTM_zone <- function(longitude, latitude) {

 # Special zones for Svalbard and Norway
    if (latitude >= 72.0 && latitude < 84.0 ) 
        if (longitude >= 0.0  && longitude <  9.0) 

ernestguevarra

Keybase proof

I hereby claim:

• I am ernestguevarra on github.
• I am ernestguevarra (https://keybase.io/ernestguevarra) on keybase.
• I have a public key ASCFyI8Wc9HTQtqwty5d2jqsjLLAmMupi_qQWphG83zzvAo

To claim this, I am signing this object:

ernestguevarra

var url = 'https://www.dfa.gov.ph/dfa-news/dfa-releasesupdate?start=1&end=2352';
var fs = require('fs');
var page = require('webpage').create();
page.open(url, function(status) {
    if (status === 'success') {
        var html = page.evaluate(function() {
            return document.documentElement.outerHTML;
        });
        try {
            fs.write("data-raw/dfaPressReleases.txt", html, 'w');