ch13

Old/SourceOld/Chapter11/chapter11.Rmd

@@ -23,7 +23,7 @@
 
 ### Footnotes
 
-Plain, non-bibliographic footnotes are easy to create in LaTeX. Simply place `\footnote{` where you would like the footnote number to apear in the text. Then type in the footnote's text and of course remember to close it with a `}`. LaTeX does the rest, including formatting and numbering.
+Plain, non-bibliographic footnotes are easy to create in LaTeX. Simply place `\footnote{` where you would like the footnote number to apear in the text. Then type in the footnote's text and Of course, remember to close it with a `}`. LaTeX does the rest, including formatting and numbering.
 
 ### Bibliographies
 

Source/Children/Chapter1/chapter1.Rnw

@@ -23,7 +23,7 @@ This book gives you the tools to dynamically combine your research with the pres
 \index{reproducible research|(}
 \index{replication|(}
 
-Though there is some debate over what are the necessary and sufficient conditions for a replication \cite[2]{Makel2014}, research results are generally considered \emph{replicable} if there is sufficient information available for independent researchers to make the same findings using the same procedures with new data.\footnote{This is close to what \cite{Lykken1968} calls ``operational replication''.} For research that relies on experiments, this can mean a researcher not involved in the original research being able to rerun the experiment, including sampling, and validate that the new results are comparable to the original ones. In computational and quantitative empirical sciences, results are replicable if independent researchers can recreate findings by following the procedures originally used to gather the data and run the computer code. Of course it is sometimes difficult to replicate the original data set because of issues such as limited resources to gather new data or because the original study already sampled the full universe of cases. \index{replication|)} So as a next-best standard we can aim for ``\emph{really reproducible research}'' \cite[1226]{Peng2011}.\footnote{The idea of really reproducible computational research was originally thought of and implemented by Jon Claerbout\index{Jon Claerbout} and the Stanford Exploration Project beginning in the 1980s and early 1990s \cite[]{Fomel2009,Donoho2009}. Further seminal advances were made by Jonathan B. Buckheit and David L. Donoho who created the Wavelab library of MATLAB\index{MATLAB} routines for their research on wavelets in the mid-1990s \cite[]{Buckheit1995}.} In computational sciences\footnote{Reproducibility is important for both quantitative and qualitative research \cite[]{King1994}. Nonetheless, we will focus mainly on on methods for reproducibility in quantitative computational research.} this means:
+Though there is some debate over what are the necessary and sufficient conditions for a replication \cite[2]{Makel2014}, research results are generally considered \emph{replicable} if there is sufficient information available for independent researchers to make the same findings using the same procedures with new data.\footnote{This is close to what \cite{Lykken1968} calls ``operational replication''.} For research that relies on experiments, this can mean a researcher not involved in the original research being able to rerun the experiment, including sampling, and validate that the new results are comparable to the original ones. In computational and quantitative empirical sciences, results are replicable if independent researchers can recreate findings by following the procedures originally used to gather the data and run the computer code. Of course, it is sometimes difficult to replicate the original data set because of issues such as limited resources to gather new data or because the original study already sampled the full universe of cases. \index{replication|)} So as a next-best standard we can aim for ``\emph{really reproducible research}'' \cite[1226]{Peng2011}.\footnote{The idea of really reproducible computational research was originally thought of and implemented by Jon Claerbout\index{Jon Claerbout} and the Stanford Exploration Project beginning in the 1980s and early 1990s \cite[]{Fomel2009,Donoho2009}. Further seminal advances were made by Jonathan B. Buckheit and David L. Donoho who created the Wavelab library of MATLAB\index{MATLAB} routines for their research on wavelets in the mid-1990s \cite[]{Buckheit1995}.} In computational sciences\footnote{Reproducibility is important for both quantitative and qualitative research \cite[]{King1994}. Nonetheless, we will focus mainly on on methods for reproducibility in quantitative computational research.} this means:
 
 \begin{quote}
     the data and code used to make a finding are available and they are sufficient for an independent researcher to recreate the finding.

Source/Children/Chapter10/chapter10.Rnw

@@ -202,7 +202,7 @@ plot(x = cars$speed, y = cars$dist,
 
 \noindent This code produces Figure \ref{BasicFigureExample}.\footnote{Note that I did not specify the center environment. This is because it is specified in a \emph{knitr} global chunk option.} If you are familiar with R graphics you will notice that we did not need to tell \emph{knitr} to save the file in a particular format. Instead, behind the scenes it automatically saves the plot as a PDF file in a folder called \emph{figure} that is a child of the current working directory. You can choose the figure file's format with the \texttt{dev} (graphical device) chunk option.\index{knitr option!dev}\label{DevTalk} For example, to save the figure in a PNG formatted file simply add the chunk option \verb|dev='PNG'|. You can choose any graphical device format supported by R. For a full list of R's graphical devices type \verb|?Devices| into your console.\index{R!graphical device} One reason you might want to change the format is to reduce your presentation document's file size. Using a bitmap format like PNG will create smaller files than PDFs, though lower-quality images.
 
-We could of course simply link to the original R source code file stored on GitHub\index{GitHub} with the \verb|source_url|\index{R function!source\_url} command. Let's look at an example of this with a different source code file. Remember in Chapter \ref{DataGather} we used a makefile to gather data from three different sources on the internet. The CSV is called \emph{MainData.csv} and is stored on GitHub at: \url{http://bit.ly/V0ldsf}.\footnote{The full version of the URL is: \url{https://raw.githubusercontent.com/christophergandrud/Rep-Res-Examples/master/DataGather_Merge/MainData.csv}} We can download this data into R and make a scatterplot matrix with this code:\index{scatterplot matrix}
+We could Of course, simply link to the original R source code file stored on GitHub\index{GitHub} with the \verb|source_url|\index{R function!source\_url} command. Let's look at an example of this with a different source code file. Remember in Chapter \ref{DataGather} we used a makefile to gather data from three different sources on the internet. The CSV is called \emph{MainData.csv} and is stored on GitHub at: \url{http://bit.ly/V0ldsf}.\footnote{The full version of the URL is: \url{https://raw.githubusercontent.com/christophergandrud/Rep-Res-Examples/master/DataGather_Merge/MainData.csv}} We can download this data into R and make a scatterplot matrix with this code:\index{scatterplot matrix}
 
 <<Ch10ScatterPlotMatrix, eval=FALSE, tidy=FALSE>>=
 # Download data
@@ -366,7 +366,7 @@ devtools::source_url("http://bit.ly/VEvGJG")
 
 \subsection{Showing regression results with caterpillar plots}
 
-Many packages that estimate statistical models from data in R have built-in plotting capabilities. For example, the \emph{survival} package \citep{R-survival} has a \texttt{plot.survfit}\index{plot.survfit} command for plotting survival curves created using event history analysis.\index{event history analysis}\index{event history analysis} These plots can of course be knitted into presentation documents like the plots we have seen already.
+Many packages that estimate statistical models from data in R have built-in plotting capabilities. For example, the \emph{survival} package \citep{R-survival} has a \texttt{plot.survfit}\index{plot.survfit} command for plotting survival curves created using event history analysis.\index{event history analysis}\index{event history analysis} These plots can Of course, be knitted into presentation documents like the plots we have seen already.
 
 However, sometimes either a package doesn't have built-in commands for plotting model results the way you want to and/or you want to use \emph{ggplot2} to improve the aesthetic quality of the plots they do create by default. In either case you can almost always create the plot that you want by first breaking into the model results object, extracting what you want, then plotting it with \emph{ggplot2}. The process is very similar to what we did in Chapter \ref{TablesChapter} to create custom tables (see Section \ref{NonSupportedClasses}).