Dysphagia

knitr::opts_chunk$set(echo = TRUE)
require(haven)

## Loading required package: haven

library(tidyr)
library(ggstatsplot)

## You can cite this package as:
##      Patil, I. (2021). Visualizations with statistical details: The 'ggstatsplot' approach.
##      Journal of Open Source Software, 6(61), 3167, doi:10.21105/joss.03167

library(ggpubr)

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library(epiDisplay)

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library(writexl)
library(readxl)
library(ggprism)
library(patchwork)

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library(magrittr)

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library(gtsummary)

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library(FSA)

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## ## FSA v0.9.4. See citation('FSA') if used in publication.
## ## Run fishR() for related website and fishR('IFAR') for related book.

library(RColorBrewer)
library(ggsci)
library(ggsignif)
library(patchwork)
library(magrittr)
library(gtsummary)
library(patchwork)
library(magrittr)
library(gtsummary)
library(dplyr)

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library(tidyverse)

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library(data.table)

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library(ggplot2)
library(epiDisplay)
library(writexl)
library(stringr)
library(SciViews)
library(trend)
library(aod)

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data <- read_excel("/Users/taylorpyle/Library/Group Containers/UBF8T346G9.OneDriveSyncClientSuite/OneDrive - University of North Carolina at Chapel Hill.noindex/OneDrive - University of North Carolina at Chapel Hill/Dr. Roberts/Dysphagia.xlsx")

data <- data %>% 
  mutate(Age=cut(Age_m, breaks=c(-Inf, 12, 24, 36, 48), labels=c("0-12 Months", "13-24 Months","25-36 Months", "26-48 Months")))

data$improvement[data$improvement == "No"] <- "N"
data$improvement[data$improvement == "x"] <- "Y"
data$Sex[data$Sex == "F"] <- "Female"
data$Sex[data$Sex == "M"] <- "Male"

data$improvement[data$improvement == "N"] <- "No Improvement"
data$improvement[data$improvement == "Y"] <- "Improvement"
data$Sex[data$Sex == "F"] <- "Female"
data$Sex[data$Sex == "M"] <- "Male"

tabledata <- data.frame(data$improvement,
                        Sex = data$Sex, 
                        Indication = data$Indication,
                        Volume = data$volume,
                        Age = data$Age,
                        Comorbidities = data$Comorbidities)

tbl_summary(tabledata, by = data.improvement) 

Characteristic	Improvement, N = 351	No Improvement, N = 111
Sex
Female	17 (49%)	6 (55%)
Male	18 (51%)	5 (45%)
Indication
Aspiration on thin liquids	15 (43%)	2 (18%)
Dysphagia	15 (43%)	6 (55%)
Laryngomalacia	2 (5.7%)	1 (9.1%)
Vocal cord paralysis	3 (8.6%)	2 (18%)
Volume
0.1	8 (23%)	4 (36%)
0.2	14 (40%)	4 (36%)
0.3	7 (20%)	1 (9.1%)
0.4	1 (2.9%)	1 (9.1%)
0.5	5 (14%)	1 (9.1%)
Age
0-12 Months	14 (40%)	4 (36%)
13-24 Months	12 (34%)	2 (18%)
25-36 Months	6 (17%)	5 (45%)
26-48 Months	3 (8.6%)	0 (0%)
Comorbidities
Ankyloglossia	4 (11%)	0 (0%)
Asthma	10 (29%)	7 (64%)
GERD	14 (40%)	2 (18%)
Preterm	6 (17%)	0 (0%)
Trisomy 21	1 (2.9%)	2 (18%)
1 n (%)

library(stargazer)

## 
## Please cite as:

##  Hlavac, Marek (2022). stargazer: Well-Formatted Regression and Summary Statistics Tables.

##  R package version 5.2.3. https://CRAN.R-project.org/package=stargazer

stargazer(tabledata, type = 'html') 

## 
## <table style="text-align:center"><tr><td colspan="6" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Statistic</td><td>N</td><td>Mean</td><td>St. Dev.</td><td>Min</td><td>Max</td></tr>
## <tr><td colspan="6" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Volume</td><td>46</td><td>0.239</td><td>0.129</td><td>0.100</td><td>0.500</td></tr>
## <tr><td colspan="6" style="border-bottom: 1px solid black"></td></tr></table>

#statistics

fisher.test(table(data$improvement, data$Age))

## 
##  Fisher's Exact Test for Count Data
## 
## data:  table(data$improvement, data$Age)
## p-value = 0.2833
## alternative hypothesis: two.sided

fisher.test(table(data$improvement, data$volume))

## 
##  Fisher's Exact Test for Count Data
## 
## data:  table(data$improvement, data$volume)
## p-value = 0.6824
## alternative hypothesis: two.sided

fisher.test(table(data$improvement, data$Sex))

## 
##  Fisher's Exact Test for Count Data
## 
## data:  table(data$improvement, data$Sex)
## p-value = 1
## alternative hypothesis: true odds ratio is not equal to 1
## 95 percent confidence interval:
##  0.158389 3.781413
## sample estimates:
## odds ratio 
##  0.7911508