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crayola <- structure(c("#EFDECD", "#CD9575", "#FDD9B5", "#78DBE2", "#87A96B", 
"#FFA474", "#FAE7B5", "#9F8170", "#FD7C6E", "#000000", "#ACE5EE", 
"#1F75FE", "#A2A2D0", "#6699CC", "#0D98BA", "#7366BD", "#DE5D83", 
"#CB4154", "#B4674D", "#FF7F49", "#EA7E5D", "#B0B7C6", "#FFFF99", 
"#1CD3A2", "#FFAACC", "#DD4492", "#1DACD6", "#BC5D58", "#DD9475", 
"#9ACEEB", "#FFBCD9", "#FDDB6D", "#2B6CC4", "#EFCDB8", "#6E5160", 
"#CEFF1D", "#71BC78", "#6DAE81", "#C364C5", "#CC6666", "#E7C697", 
"#FCD975", "#A8E4A0", "#95918C", "#1CAC78", "#1164B4", "#F0E891", 
"#FF1DCE", "#B2EC5D", "#5D76CB", "#CA3767", "#3BB08F", "#FEFE22", 
"#FCB4D5", "#FFF44F", "#FFBD88", "#F664AF", "#AAF0D1", "#CD4A4C", 

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library(boot)
r2 = function(f, d, i) {
  d = d[i, ]
  f = lm(f, data = d)
  return(summary(f)$r.square)
}
br <- boot(COI, r2, 10000, formula = nb.publis ~ nb.liens)
br 
plot(br)
boot.ci(br, .95, "bca")

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require(downloader)

# PJ example.
link = "https://raw.github.com/pedroj/bipartite_plots/master/data/NCH_quant_bmatrix.txt"
file = "data/NCH_quant_bmatrix.txt"
if(!file.exists(file)) download(link, file, mode = "wb")
M <- read.table(file, sep = "\t", dec = ",", header = TRUE, row.names = 1)

#
# Bipartite network initialization, starting from an adjacency matrix.

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> # Get data for 2011
> query <- c("cbt" = "'cognitive behavior therapy' OR 'cognitive behavioral therapy' OR 'cognitive therapy' AND 2011[DP]")
> pub.efetch <- searchPubmed(query)
Searching (downloading 1718 articles)
Completed download from PubMed.
> cbt_2011 <- extractJournal()
XML declaration allowed only at the start of the document
StartTag: invalid element name
Error: 1: XML declaration allowed only at the start of the document
2: StartTag: invalid element name

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An extrapolation of this blog post.

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a { color: #264EC0; }
b { color: #D22310; }
c { color: #FC8608; }
d { color: #168713; }
e { color: #850086; }
f { color: #1086B9; }
g { color: #D22B63; }
h { color: #559D05; }
i { color: #A71B23; }
j { color: #21436F; }

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Here are little chunks of R code to quickly access survey datasets. Some of the linked datasets are provided on an "as-is" basis: typically, you might want to check the official ANES files rather than rely on the extracts linked to below. This also applies to data extracts bundled in packages.

HOWTO

The code occasionally calls the download and foreign packages, respectively to get files from HTTPS sources and to deal with foreign formats. The Gelman and Hill replication also uses plyr and ggplot2, but check the original code for identical functions written in base R.

SEEALSO

• Anthony J. Damico's usgsd repository of scripts for survey microdata analysis; ref.; [how it compares](https://github.com/ajd

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This Gist is used to create the variable indexes in this package:

1. Stata do-file to extract the variable labels
2. R script to convert the files to R data frames.
3. R script to create the demo datasets.

The scripts all worked in early August 2013.

Exceptions corrected by the do-file:

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------------------------------------------------------------------------------------
      name:  srqm_demo
       log:  /Users/fr/Documents/Teaching/SRQM/demo.log
  log type:  text
 opened on:  17 Aug 2013, 18:28:28

. 
. * Check setup. This line appears in every course do-file. It makes sure that
. * you have the appropriate files and packages to successfully run the code.
. run setup/require fre lookfor_all

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You will need to insert your authentification token where the code says [TOKEN].

The data availability ranges from null to full in function of the country of interest:

Here's a quick plot of the 90/10 percentile ratio for European countries: