\documentclass[a4paper]{article}
\usepackage{booktabs,dcolumn}

\begin{document}

We fit a linear regression for the economic journals demand model.

<<regression>>=
data("Journals", package = "AER")
journals_lm <- lm(log(subs) ~ log(price/citations), data = Journals)
journals_lm
@

A scatter plot with the fitted regression line is shown in Figure~\ref{fig:fig1} below.

\begin{figure}[h]
\begin{center}
<<visualization, echo=FALSE, fig=TRUE, height=5, width=6>>=
plot(log(subs) ~ log(price/citations), data = Journals)
abline(journals_lm)
@
\caption{\label{fig:fig1} Scatter plot with fitted regression line for the \texttt{Journals} data.}
\end{center}
\end{figure}

The fitted regression line is

\[
  \log(\mbox{subscriptions}) \quad = \quad
    \Sexpr{round(coef(journals_lm)[1], digits = 2)}
    \Sexpr{if(coef(journals_lm)[2] < 0) "-" else "+"}
    \Sexpr{abs(round(coef(journals_lm)[2], digits = 2))}
    \cdot \log(\mbox{price per citation})
\]

Table~\ref{tab:journals1} summarizes the results of the model along with a slightly
extended model in type of table commonly used in economics and social science
publications. This can be easily produced with the \emph{memisc} package. Alternative
packages for producing such tables are \emph{texreg} or \emph{stargazer}.

\begin{table}[h]
\begin{center}
\caption{\label{tab:journals1} Automatic regression summaries for \texttt{Journals} data (via \emph{memisc}).}
<<summary-table2, echo=FALSE, results=tex>>=
journals_lm2 <- lm(log(subs) ~ log(price/citations) + foundingyear, data = Journals)
library("memisc")
toLatex(mtable("Model 1" = journals_lm, "Model 2" = journals_lm2,
  summary.stats = c("N", "R-squared", "BIC")))
@
\end{center}
\end{table}


Furthermore, it may also be necessary (and not too hard) to generate the table ``by hand'' using
text manipulation in R. See Table~\ref{tab:journals2}.

\begin{table}[h]
\begin{center}
\caption{\label{tab:journals2} Hand-crafted regression summary for \texttt{Journals} data.}
\begin{tabular}{rrrrr}
\hline
& Estimate & Std.~error & $t$ statistic & $p$ value \\
\hline
<<summary-table, echo=FALSE, results=tex>>=
x <- summary(journals_lm)$coefficients
x[] <- as.character(round(x, digits = 3))
x[,4] <- ifelse(as.numeric(x[,4]) < 0.001, "< 0.001", x[,4])
cat(paste(rownames(x), "& $",
  apply(x, 1, paste, collapse = "$ & $"), "$\\\\ \n"))
@
\hline
\end{tabular}
\end{center}
\end{table}

Finally, summaries of a single model can also be automatically generated by the \emph{xtable} package,
see Table~\ref{tab:journals3}.

<<summary-table2, echo=FALSE, results=tex>>=
library("xtable")
print(
  xtable(journals_lm,
    caption = "Automatic regression summary for \\texttt{Journals} data (via \\emph{xtable}).",
    label = "tab:journals3"),
  caption.placement = "top")
@

\end{document}