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update latex format for r output

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lukasadrion
2026-02-06 01:25:30 +01:00
parent 97b40d8c18
commit 03c40a3a96
1 changed files with 51 additions and 23 deletions
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74
doc/report.Rnw
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@@ -2,6 +2,7 @@
\usepackage{graphicx} % for including figures
\usepackage{booktabs} % for nicer tables
\usepackage{float}
\begin{document}
@@ -21,25 +22,25 @@ Three on-screen keyboard layouts were evaluated in this study: QWERTY, Dvorak, a
This design allowed us to investigate both established and novel layouts, comparing objective typing performance, error rates, and subjective workload.
\begin{figure}[h]
\begin{figure}[H]
\centering
\includegraphics[width=0.5\textwidth]{images/qwerty-pic.png}
\includegraphics[width=0.45\textwidth]{images/qwerty-pic.png}
\caption{QWERTY Keyboard Layout}
\label{fig:qwerty}
\end{figure}
\begin{figure}[h]
\begin{figure}[H]
\centering
\includegraphics[width=0.6\textwidth]{images/dvorak-pic.png}
\includegraphics[width=0.45\textwidth]{images/dvorak-pic.png}
\caption{Dvorak Keyboard Layout}
\label{fig:dvorak}
\end{figure}
\begin{figure}[h]
\begin{figure}[H]
\centering
\includegraphics[width=0.4\textwidth]{images/circle-pic.png}
\includegraphics[width=0.3\textwidth]{images/circle-pic.png}
\caption{Circle Keyboard Layout}
\label{fig:circle}
\end{figure}
@@ -71,7 +72,7 @@ wpm <- summary(results[, c("qwerty_wpm", "dvorak_wpm", "circle_wpm")])
@
% TER table
\begin{table}[h]
\begin{table}[H]
\centering
\scriptsize
<<results='asis', echo=FALSE>>=
@@ -81,7 +82,7 @@ kable(ter, format="latex", booktabs=TRUE)
\end{table}
% WPM table
\begin{table}[h]
\begin{table}[H]
\centering
\scriptsize
<<results='asis', echo=FALSE>>=
@@ -90,7 +91,7 @@ kable(wpm, format="latex", booktabs=TRUE)
\caption{Summary of Words per Minute (WPM)}
\end{table}
<<echo=FALSE>>=
<<echo=FALSE, results='hide'>>=
# Create figures directory if it doesn't exist
dir.create("../figures", showWarnings=FALSE)
@@ -116,7 +117,7 @@ ter_stats <- rbind(
)
# Save TER barplot as PDF using LaTeX-compatible fonts
pdf("../figures/ter_plot.pdf")
suppressMessages(pdf("../figures/ter_plot.pdf"))
bar_pos <- barplot(
ter_stats[,"mean"],
names.arg=c("QWERTY","DVORAK","CIRCLE"),
@@ -140,7 +141,7 @@ wpm_stats <- rbind(
)
# Save WPM barplot as PDF using LaTeX-compatible fonts
pdf("../figures/wpm_plot.pdf")
suppressMessages(pdf("../figures/wpm_plot.pdf"))
bar_pos <- barplot(
wpm_stats[,"mean"],
names.arg=c("QWERTY","DVORAK","CIRCLE"),
@@ -157,14 +158,14 @@ dev.off()
@
% Include TER plot
\begin{figure}[h]
\begin{figure}[H]
\centering
\includegraphics[width=\columnwidth]{../figures/ter_plot.pdf}
\caption{Total Error Rate (TER) by Keyboard Layout}
\end{figure}
% Include WPM plot
\begin{figure}[h]
\begin{figure}[H]
\centering
\includegraphics[width=\columnwidth]{../figures/wpm_plot.pdf}
\caption{Words per Minute (WPM) by Keyboard Layout}
@@ -172,13 +173,13 @@ dev.off()
\subsubsection{Subjective Measures}\label{subjective-measures}
<<echo=FALSE>>=
<<echo=FALSE, results='hide'>>=
# Read NASA-TLX data
nasa <- read.csv("../data/nasaTLX.csv")
nasa$layout <- factor(nasa$layout)
# Save boxplots as PDF using LaTeX-compatible fonts
pdf("../figures/nasa_boxplots.pdf")
suppressMessages(pdf("../figures/nasa_boxplots.pdf"))
par(mfrow=c(2,3)) # Arrange plots in 2 rows x 3 columns
boxplot(mental_demand ~ layout, data=nasa, main="Mental Demand")
boxplot(physical_demand ~ layout, data=nasa, main="Physical Demand")
@@ -190,7 +191,7 @@ dev.off()
@
% Include NASA-TLX boxplots
\begin{figure}[h]
\begin{figure}[H]
\centering
\includegraphics[width=\columnwidth]{../figures/nasa_boxplots.pdf}
\caption{NASA-TLX Scores by Keyboard Layout}
@@ -208,9 +209,9 @@ Dependent var:
- Nasa-TLX
%Anova RM for WPM
<<echo=FALSE>>=
<<echo=FALSE, results='hide'>>=
library(tidyr)
library(dplyr)
suppressMessages(library(dplyr))
# Add participant ID
results$id <- 1:nrow(results)
@@ -232,13 +233,28 @@ wpm_long$layout <- factor(wpm_long$layout,
# --- RM ANOVA for WPM ---
anova_wpm <- aov(wpm ~ layout + Error(id/layout), data=wpm_long)
@
Anova WPM results:
<<results='asis', echo=FALSE>>=
library(knitr)
wpm_tab <- summary(anova_wpm)[[2]][[1]]
# Print ANOVA table
summary(anova_wpm)
wpm_effect <- wpm_tab["layout", , drop=FALSE]
wpm_effect$`Pr(>F)` <- "$p< .001$"
colnames(wpm_effect) <- c("Df", "Sum Sq", "Mean Sq", "F value", "p-value")
kable(wpm_effect,
format="latex",
booktabs=TRUE,
caption="Layout Effect on WPM",
escape=FALSE)
@
%Anova RM for TER
<<echo=FALSE>>=
<<echo=FALSE, results='hide'>>=
# --- TER Long Format ---
ter_long <- results %>%
@@ -257,12 +273,24 @@ ter_long$layout <- factor(ter_long$layout,
# --- RM ANOVA for TER ---
anova_ter <- aov(ter ~ layout + Error(id/layout), data=ter_long)
@
Anova TER results:
<<results='asis', echo=FALSE>>=
ter_tab <- summary(anova_ter)[[2]][[1]]
summary(anova_ter)
ter_effect <- ter_tab["layout", , drop=FALSE]
colnames(ter_effect) <- c("Df", "Sum Sq", "Mean Sq", "F value", "p-value")
kable(ter_effect,
format="latex",
booktabs=TRUE,
caption="Repeated-Measures ANOVA for TER")
@
% Post-Hoc analysis with bonferroni correction for WPM
<<echo=FALSE>>=
<<echo=FALSE, results='hide'>>=
suppressMessages(library(emmeans))
suppressMessages(emm_wpm <- emmeans(anova_wpm, ~ layout))