clinical_report.Rnw

\documentclass{article}
\usepackage{geometry}
\usepackage{graphicx}
\usepackage{hyperref}
\usepackage{booktabs} % Required for xtable aesthetics

\title{Phase III Clinical Trial Analysis}
\author{Bioinformatics Division}

\begin{document}
\maketitle

\section{Statistical Analysis Protocol}

We investigate the efficacy of Treatment A vs. Placebo. The analysis is performed using R version \Sexpr{getRversion()}.

% Global Chunk Options
% echo=TRUE: Show R code in the document (transparency)
% warning=FALSE: Suppress warning messages in final PDF
% dev='pdf': Generate high-quality vector graphics
<<setup, include=FALSE>>=
library(knitr)
library(ggplot2)
library(xtable)
opts_chunk$set(echo=TRUE, warning=FALSE, message=FALSE, dev='pdf', fig.width=6, fig.height=4)
@

\section{Data Ingestion and Summary}

<<data_load, results='asis'>>=
# Simulate Clinical Data
set.seed(2024)
n <- 50
df <- data.frame(
  id = 1:(2*n),
  group = factor(rep(c("Placebo", "Treatment"), each=n)),
  recovery_days = c(rnorm(n, mean=14, sd=3), rnorm(n, mean=10, sd=2.5))
)

# Descriptive Statistics Table
summary_stats <- aggregate(recovery_days ~ group, data=df, FUN=function(x) c(Mean=mean(x), SD=sd(x)))
summary_stats <- do.call(data.frame, summary_stats) # Flatten structure

# Print as LaTeX table using xtable
print(xtable(summary_stats, caption="Descriptive Statistics by Group"),
      booktabs=TRUE, include.rownames=FALSE)
@

The table above is generated dynamically. If the underlying dataset \texttt{df} changes, the table updates automatically without manual re-formatting.

\section{Hypothesis Testing and Visualization}

We perform an independent t-test to compare the groups.

<<ttest, echo=FALSE>>=
test_result <- t.test(recovery_days ~ group, data=df)
pval <- test_result$p.value
@

The t-test yields a p-value of \Sexpr{format.pval(pval, eps=0.001)}.
\Sexpr{ifelse(pval < 0.05, "This indicates a statistically significant difference.", "This result is not significant.")}

<<boxplot, fig.cap="Distribution of Recovery Days by Treatment Group">>=
ggplot(df, aes(x=group, y=recovery_days, fill=group)) +
  geom_boxplot(alpha=0.7) +
  geom_jitter(width=0.2, alpha=0.5) +
  theme_minimal() +
  labs(y="Days to Recovery", x="Study Group") +
  scale_fill_brewer(palette="Pastel1")
@

\end{document}