Data Quality Assessment and Exploration
Source:vignettes/clinicopath-descriptives-02-data-quality.Rmd
clinicopath-descriptives-02-data-quality.RmdIntroduction
Data quality assessment is fundamental to reliable clinical research. This vignette demonstrates essential data exploration and quality assessment techniques using ClinicoPathDescriptives.
Basic Setup
library(ClinicoPath)
library(dplyr)
library(tidyr)
library(ggplot2)
library(knitr)
# Load the dataset
data(histopathology)
# Initial data overview
cat("Dataset Dimensions:", dim(histopathology), "\n")
#> Dataset Dimensions: 250 38
cat("Variables:", ncol(histopathology), "\n")
#> Variables: 38
cat("Observations:", nrow(histopathology), "\n\n")
#> Observations: 250Phase 1: Completeness Assessment
Missing Data Analysis
# Calculate missing data percentages
missing_summary <- histopathology %>%
summarise_all(~sum(is.na(.))) %>%
pivot_longer(everything(), names_to = "Variable", values_to = "Missing_Count") %>%
mutate(
Missing_Percentage = round(Missing_Count / nrow(histopathology) * 100, 1),
Data_Quality = case_when(
Missing_Percentage == 0 ~ "Complete",
Missing_Percentage <= 5 ~ "Excellent",
Missing_Percentage <= 10 ~ "Good",
Missing_Percentage <= 20 ~ "Acceptable",
TRUE ~ "Poor"
)
) %>%
arrange(desc(Missing_Percentage))
# Display missing data summary
kable(missing_summary %>% filter(Missing_Count > 0),
caption = "Missing Data Summary",
col.names = c("Variable", "Missing Count", "Missing %", "Quality Rating"))| Variable | Missing Count | Missing % | Quality Rating |
|---|---|---|---|
| OverallTime | 2 | 0.8 | Excellent |
| Name | 1 | 0.4 | Excellent |
| Sex | 1 | 0.4 | Excellent |
| Age | 1 | 0.4 | Excellent |
| Race | 1 | 0.4 | Excellent |
| PreinvasiveComponent | 1 | 0.4 | Excellent |
| LVI | 1 | 0.4 | Excellent |
| PNI | 1 | 0.4 | Excellent |
| LastFollowUpDate | 1 | 0.4 | Excellent |
| Death | 1 | 0.4 | Excellent |
| Group | 1 | 0.4 | Excellent |
| Grade | 1 | 0.4 | Excellent |
| TStage | 1 | 0.4 | Excellent |
| Anti-X-intensity | 1 | 0.4 | Excellent |
| Anti-Y-intensity | 1 | 0.4 | Excellent |
| LymphNodeMetastasis | 1 | 0.4 | Excellent |
| Valid | 1 | 0.4 | Excellent |
| Smoker | 1 | 0.4 | Excellent |
| Grade_Level | 1 | 0.4 | Excellent |
| SurgeryDate | 1 | 0.4 | Excellent |
| Outcome | 1 | 0.4 | Excellent |
| Mortality5yr | 1 | 0.4 | Excellent |
| Rater 1 | 1 | 0.4 | Excellent |
Phase 2: Distribution Assessment
Continuous Variables Analysis
# Analyze distributions of continuous variables
continuous_vars <- c("Age", "OverallTime", "MeasurementA", "MeasurementB")
# Basic summary statistics
summary(histopathology[continuous_vars])
#> Age OverallTime MeasurementA MeasurementB
#> Min. :25.00 Min. : 2.90 Min. :-2.49830 Min. :-0.7433
#> 1st Qu.:38.00 1st Qu.: 7.10 1st Qu.:-0.52699 1st Qu.: 0.6105
#> Median :49.00 Median :10.15 Median : 0.09627 Median : 0.9788
#> Mean :49.44 Mean :16.52 Mean : 0.07203 Mean : 0.9668
#> 3rd Qu.:62.00 3rd Qu.:23.60 3rd Qu.: 0.68241 3rd Qu.: 1.3542
#> Max. :73.00 Max. :58.20 Max. : 2.29156 Max. : 2.5662
#> NA's :1 NA's :2
# Check for normality and distribution patterns
cat("\nDistribution Assessment:\n")
#>
#> Distribution Assessment:
for(var in continuous_vars) {
if(var %in% names(histopathology)) {
cat(paste(var, "- Mean:", round(mean(histopathology[[var]], na.rm = TRUE), 2),
"SD:", round(sd(histopathology[[var]], na.rm = TRUE), 2), "\n"))
}
}
#> Age - Mean: 49.44 SD: 13.81
#> OverallTime - Mean: 16.53 SD: 13.5
#> MeasurementA - Mean: 0.07 SD: 0.87
#> MeasurementB - Mean: 0.97 SD: 0.56Categorical Variables Analysis
# Analyze categorical variable distributions
categorical_vars <- c("Sex", "Grade", "TStage", "Group", "LVI", "PNI")
# Basic frequency tables for categorical variables
cat("Categorical Variables Distribution:\n\n")
#> Categorical Variables Distribution:
for(var in categorical_vars) {
if(var %in% names(histopathology)) {
cat(paste("==", var, "==\n"))
print(table(histopathology[[var]], useNA = "ifany"))
cat("\n")
}
}
#> == Sex ==
#>
#> Female Male <NA>
#> 121 128 1
#>
#> == Grade ==
#>
#> 1 2 3 <NA>
#> 74 76 99 1
#>
#> == TStage ==
#>
#> 1 2 3 4 <NA>
#> 24 51 63 111 1
#>
#> == Group ==
#>
#> Control Treatment <NA>
#> 120 129 1
#>
#> == LVI ==
#>
#> Absent Present <NA>
#> 143 106 1
#>
#> == PNI ==
#>
#> Absent Present <NA>
#> 166 83 1Phase 3: Quality Assessment with ClinicoPath Functions
Cross-tabulation Analysis
# Example of proper crosstable usage
crosstable(
data = histopathology,
vars = c("Grade", "TStage"),
group = "Group"
)
#>
#> CROSS TABLE
#>
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#>
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#> <div class="caption">Cross Table for Dependent group<div
#> class="figbody"><table class="tangram">
#> <th class="header even tg-label"><span class="variable"><th
#> class="header even tg-label"><span class="variable">N<th class="header
#> even tg-label"><span class="variable">Control<th class="header even
#> tg-label"><span class="variable">Treatment<th class="header even
#> tg-label"><span class="variable">Test Statistic<tr
#> class="subheaderrow"><th class="subheader header even tg-label"><span
#> class="variable"><th class="subheader header even tg-label"><span
#> class="variable"><th class="subheader header even data N"><span
#> class="N">(N=120)<th class="subheader header even data N"><span
#> class="N">(N=129)<th class="subheader header even tg-label"><span
#> class="variable">
#> <td class="header odd tg-label"><span class="variable">Grade<td
#> class="odd data N"><span class="N">249<td class="odd">1.0 2.0 3.0<td
#> class="odd">1.0 2.0 3.0<td class="statistics odd">F1,246=0.74, P=0.393
#> <td class="header even tg-label"><span class="variable">TStage<td
#> class="even data N"><span class="N">249<td class="even">2.0 3.0 4.0<td
#> class="even">2.0 3.0 4.0<td class="statistics even">F1,246=0.03,
#> P=0.863
#> <div class="footnote">N is the number of non-missing value.
#> 1Kruskal-Wallis. 2Pearson. 3Wilcoxon.Data Summary
# Example of proper summarydata usage
summarydata(
data = histopathology,
vars = c("Age", "OverallTime"),
date_vars = character(0),
grvar = "Group"
)
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#> #dfieexombw .gt_indent_5 {
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#> #dfieexombw .katex-display {
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#> margin-bottom: 0.75em !important;
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#> <thead>
#> <tr class="gt_heading">
#> <td colspan="7" class="gt_heading gt_title gt_font_normal" style>.</td>
#> </tr>
#> <tr class="gt_heading">
#> <td colspan="7" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>250 rows x 3 cols</td>
#> </tr>
#> <tr class="gt_col_headings">
#> <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1" scope="col" id="type"></th>
#> <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1" scope="col" id="name">Column</th>
#> <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1" scope="col" id="value">Plot Overview</th>
#> <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" scope="col" id="n_missing">Missing</th>
#> <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" scope="col" id="Mean">Mean</th>
#> <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" scope="col" id="Median">Median</th>
#> <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" scope="col" id="SD">SD</th>
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#> </thead>
#> <tbody class="gt_table_body">
#> <tr><td headers="type" class="gt_row gt_left"><svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:20px;width:25px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#f18e2c;overflow:visible;position:relative;"><path d="M576 0c17.7 0 32 14.3 32 32V480c0 17.7-14.3 32-32 32s-32-14.3-32-32V32c0-17.7 14.3-32 32-32zM448 96c17.7 0 32 14.3 32 32V480c0 17.7-14.3 32-32 32s-32-14.3-32-32V128c0-17.7 14.3-32 32-32zM352 224V480c0 17.7-14.3 32-32 32s-32-14.3-32-32V224c0-17.7 14.3-32 32-32s32 14.3 32 32zM192 288c17.7 0 32 14.3 32 32V480c0 17.7-14.3 32-32 32s-32-14.3-32-32V320c0-17.7 14.3-32 32-32zM96 416v64c0 17.7-14.3 32-32 32s-32-14.3-32-32V416c0-17.7 14.3-32 32-32s32 14.3 32 32z"/></svg></td>
#> <td headers="name" class="gt_row gt_left" style="font-weight: bold;">Age</td>
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#> <td headers="n_missing" class="gt_row gt_right">0.4%</td>
#> <td headers="Mean" class="gt_row gt_right">49.4</td>
#> <td headers="Median" class="gt_row gt_right">49.0</td>
#> <td headers="SD" class="gt_row gt_right">13.8</td></tr>
#> <tr><td headers="type" class="gt_row gt_left gt_striped"><svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:20px;width:25px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#f18e2c;overflow:visible;position:relative;"><path d="M576 0c17.7 0 32 14.3 32 32V480c0 17.7-14.3 32-32 32s-32-14.3-32-32V32c0-17.7 14.3-32 32-32zM448 96c17.7 0 32 14.3 32 32V480c0 17.7-14.3 32-32 32s-32-14.3-32-32V128c0-17.7 14.3-32 32-32zM352 224V480c0 17.7-14.3 32-32 32s-32-14.3-32-32V224c0-17.7 14.3-32 32-32s32 14.3 32 32zM192 288c17.7 0 32 14.3 32 32V480c0 17.7-14.3 32-32 32s-32-14.3-32-32V320c0-17.7 14.3-32 32-32zM96 416v64c0 17.7-14.3 32-32 32s-32-14.3-32-32V416c0-17.7 14.3-32 32-32s32 14.3 32 32z"/></svg></td>
#> <td headers="name" class="gt_row gt_left gt_striped" style="font-weight: bold;">OverallTime</td>
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#> <td headers="n_missing" class="gt_row gt_right gt_striped">0.8%</td>
#> <td headers="Mean" class="gt_row gt_right gt_striped">16.5</td>
#> <td headers="Median" class="gt_row gt_right gt_striped">10.1</td>
#> <td headers="SD" class="gt_row gt_right gt_striped">13.5</td></tr>
#> <tr><td headers="type" class="gt_row gt_left"><svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:20px;width:20px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#4e79a7;overflow:visible;position:relative;"><path d="M40 48C26.7 48 16 58.7 16 72v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V72c0-13.3-10.7-24-24-24H40zM192 64c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zm0 160c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zm0 160c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zM16 232v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V232c0-13.3-10.7-24-24-24H40c-13.3 0-24 10.7-24 24zM40 368c-13.3 0-24 10.7-24 24v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V392c0-13.3-10.7-24-24-24H40z"/></svg></td>
#> <td headers="name" class="gt_row gt_left" style="font-weight: bold;"><div style='max-width: 150px;'>
#> <details style='font-weight: normal !important;'>
#> <summary style='font-weight: bold !important;'>Group</summary>
#> Treatment and Control
#> </details></div></td>
#> <td headers="value" class="gt_row gt_center"><?xml version='1.0' encoding='UTF-8' ?><svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' width='141.73pt' height='34.02pt' viewBox='0 0 141.73 34.02'><g class='svglite'><defs> <style type='text/css'><![CDATA[ .svglite line, .svglite polyline, .svglite polygon, .svglite path, .svglite rect, .svglite circle { fill: none; stroke: #000000; stroke-linecap: round; stroke-linejoin: round; stroke-miterlimit: 10.00; } .svglite text { white-space: pre; } .svglite g.glyphgroup path { fill: inherit; stroke: none; } ]]></style></defs><rect width='100%' height='100%' style='stroke: none; fill: none;'/><defs> <clipPath id='cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg=='> <rect x='0.00' y='0.00' width='141.73' height='34.02' /> </clipPath></defs><g clip-path='url(#cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg==)'></g><defs> <clipPath id='cpMS4wMHwxNDAuNzR8Mi45OXwyMy42MQ=='> <rect x='1.00' y='2.99' width='139.74' height='20.62' /> </clipPath></defs><g clip-path='url(#cpMS4wMHwxNDAuNzR8Mi45OXwyMy42MQ==)'><rect x='73.39' y='3.93' width='67.34' height='18.75' style='stroke-width: 1.07; stroke: none; stroke-linecap: butt; stroke-linejoin: miter; fill: #DDEAF7;' /><rect x='1.00' y='3.93' width='72.40' height='18.75' style='stroke-width: 1.07; stroke: none; stroke-linecap: butt; stroke-linejoin: miter; fill: #3181BD;' /></g><g clip-path='url(#cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg==)'><text x='1.00' y='30.18' style='font-size: 8.00px; font-family: "Arial";' textLength='43.61px' lengthAdjust='spacingAndGlyphs'>2 categories</text></g></g></svg></td>
#> <td headers="n_missing" class="gt_row gt_right">0.4%</td>
#> <td headers="Mean" class="gt_row gt_right">—</td>
#> <td headers="Median" class="gt_row gt_right">—</td>
#> <td headers="SD" class="gt_row gt_right">—</td></tr>
#> </tbody>
#>
#>
#> </table>
#> </div>
#>
#> SUMMARY OF CONTINUOUS VARIABLES
#>
#> character(0)
#>
#> *Group: Control*
#> Mean of Age is: 49.8 ± 14.4. (Median: 49.5 [Min: 26 - Max: 73])
#>
#> *Group: Control*
#> Mean of OverallTime is: 16.2 ± 13.6. (Median: 9.8 [Min: 2.9 - Max:
#> 57.7])
#>
#> *Group: Treatment*
#> Mean of Age is: 49 ± 13.3. (Median: 49 [Min: 25 - Max: 73])
#>
#> *Group: Treatment*
#> Mean of OverallTime is: 16.9 ± 13.5. (Median: 10.6 [Min: 3.1 - Max:
#> 58.2])
#>
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#>
#> <tr class="gt_heading">
#> <td colspan="7" class="gt_heading gt_subtitle gt_font_normal
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#>
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#> font-family: "Courier";' textLength='25.16px'
#> lengthAdjust='spacingAndGlyphs'>73 auto
#> <td headers="n_missing" class="gt_row gt_right">0.4%
#> <td headers="Mean" class="gt_row gt_right">49.4
#> <td headers="Median" class="gt_row gt_right">49.0
#> <td headers="SD" class="gt_row gt_right">13.8
#> <td headers="type" class="gt_row gt_left gt_striped"><svg
#> aria-hidden="true" role="img" viewBox="0 0 640 512"
#> style="height:20px;width:25px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#f18e2c;overflow:visible;position:relative;"><path
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#> <td headers="name" class="gt_row gt_left gt_striped"
#> style="font-weight: bold;">OverallTime
#> <td headers="value" class="gt_row gt_center gt_striped"><?xml
#> version='1.0' encoding='UTF-8' ?><svg
#> xmlns='http://www.w3.org/2000/svg'
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#> <td headers="n_missing" class="gt_row gt_right gt_striped">0.8%
#> <td headers="Mean" class="gt_row gt_right gt_striped">16.5
#> <td headers="Median" class="gt_row gt_right gt_striped">10.1
#> <td headers="SD" class="gt_row gt_right gt_striped">13.5
#> <td headers="type" class="gt_row gt_left"><svg aria-hidden="true"
#> role="img" viewBox="0 0 512 512"
#> style="height:20px;width:20px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#4e79a7;overflow:visible;position:relative;"><path
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#> <td headers="name" class="gt_row gt_left" style="font-weight:
#> bold;"><div style='max-width: 150px;'>
#> <details style='font-weight: normal !important;'>
#> <summary style='font-weight: bold !important;'>Group
#> Treatment and Control
#>
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#> encoding='UTF-8' ?><svg xmlns='http://www.w3.org/2000/svg'
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#> <td headers="n_missing" class="gt_row gt_right">0.4%
#> <td headers="Mean" class="gt_row gt_right">—
#> <td headers="Median" class="gt_row gt_right">—
#> <td headers="SD" class="gt_row gt_right">—Categorical Reporting
# Example of proper reportcat usage
reportcat(
data = histopathology,
vars = c("Sex", "Grade", "LVI", "PNI")
)
#> <div id="kkeulbfdpb" style="padding-left:0px;padding-right:0px;padding-top:10px;padding-bottom:10px;overflow-x:auto;overflow-y:auto;width:auto;height:auto;">
#> <style>@import url("https://fonts.googleapis.com/css2?family=Lato:ital,wght@0,100;0,200;0,300;0,400;0,500;0,600;0,700;0,800;0,900;1,100;1,200;1,300;1,400;1,500;1,600;1,700;1,800;1,900&display=swap");
#> #kkeulbfdpb table {
#> font-family: Lato, system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji';
#> -webkit-font-smoothing: antialiased;
#> -moz-osx-font-smoothing: grayscale;
#> }
#>
#> #kkeulbfdpb thead, #kkeulbfdpb tbody, #kkeulbfdpb tfoot, #kkeulbfdpb tr, #kkeulbfdpb td, #kkeulbfdpb th {
#> border-style: none;
#> }
#>
#> #kkeulbfdpb p {
#> margin: 0;
#> padding: 0;
#> }
#>
#> #kkeulbfdpb .gt_table {
#> display: table;
#> border-collapse: collapse;
#> line-height: normal;
#> margin-left: auto;
#> margin-right: auto;
#> color: #333333;
#> font-size: 16px;
#> font-weight: normal;
#> font-style: normal;
#> background-color: #FFFFFF;
#> width: auto;
#> border-top-style: solid;
#> border-top-width: 3px;
#> border-top-color: #FFFFFF;
#> border-right-style: none;
#> border-right-width: 2px;
#> border-right-color: #D3D3D3;
#> border-bottom-style: solid;
#> border-bottom-width: 2px;
#> border-bottom-color: #A8A8A8;
#> border-left-style: none;
#> border-left-width: 2px;
#> border-left-color: #D3D3D3;
#> }
#>
#> #kkeulbfdpb .gt_caption {
#> padding-top: 4px;
#> padding-bottom: 4px;
#> }
#>
#> #kkeulbfdpb .gt_title {
#> color: #333333;
#> font-size: 24px;
#> font-weight: initial;
#> padding-top: 4px;
#> padding-bottom: 4px;
#> padding-left: 5px;
#> padding-right: 5px;
#> border-bottom-color: #FFFFFF;
#> border-bottom-width: 0;
#> }
#>
#> #kkeulbfdpb .gt_subtitle {
#> color: #333333;
#> font-size: 85%;
#> font-weight: initial;
#> padding-top: 3px;
#> padding-bottom: 5px;
#> padding-left: 5px;
#> padding-right: 5px;
#> border-top-color: #FFFFFF;
#> border-top-width: 0;
#> }
#>
#> #kkeulbfdpb .gt_heading {
#> background-color: #FFFFFF;
#> text-align: left;
#> border-bottom-color: #FFFFFF;
#> border-left-style: none;
#> border-left-width: 1px;
#> border-left-color: #D3D3D3;
#> border-right-style: none;
#> border-right-width: 1px;
#> border-right-color: #D3D3D3;
#> }
#>
#> #kkeulbfdpb .gt_bottom_border {
#> border-bottom-style: solid;
#> border-bottom-width: 0px;
#> border-bottom-color: #D3D3D3;
#> }
#>
#> #kkeulbfdpb .gt_col_headings {
#> border-top-style: solid;
#> border-top-width: 0px;
#> border-top-color: #D3D3D3;
#> border-bottom-style: solid;
#> border-bottom-width: 2px;
#> border-bottom-color: #D3D3D3;
#> border-left-style: none;
#> border-left-width: 1px;
#> border-left-color: #D3D3D3;
#> border-right-style: none;
#> border-right-width: 1px;
#> border-right-color: #D3D3D3;
#> }
#>
#> #kkeulbfdpb .gt_col_heading {
#> color: #333333;
#> background-color: #FFFFFF;
#> font-size: 80%;
#> font-weight: bolder;
#> text-transform: uppercase;
#> border-left-style: none;
#> border-left-width: 1px;
#> border-left-color: #D3D3D3;
#> border-right-style: none;
#> border-right-width: 1px;
#> border-right-color: #D3D3D3;
#> vertical-align: bottom;
#> padding-top: 5px;
#> padding-bottom: 6px;
#> padding-left: 5px;
#> padding-right: 5px;
#> overflow-x: hidden;
#> }
#>
#> #kkeulbfdpb .gt_column_spanner_outer {
#> color: #333333;
#> background-color: #FFFFFF;
#> font-size: 80%;
#> font-weight: bolder;
#> text-transform: uppercase;
#> padding-top: 0;
#> padding-bottom: 0;
#> padding-left: 4px;
#> padding-right: 4px;
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#>
#> #kkeulbfdpb .gt_column_spanner_outer:first-child {
#> padding-left: 0;
#> }
#>
#> #kkeulbfdpb .gt_column_spanner_outer:last-child {
#> padding-right: 0;
#> }
#>
#> #kkeulbfdpb .gt_column_spanner {
#> border-bottom-style: solid;
#> border-bottom-width: 2px;
#> border-bottom-color: #D3D3D3;
#> vertical-align: bottom;
#> padding-top: 5px;
#> padding-bottom: 5px;
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#> #kkeulbfdpb .gt_spanner_row {
#> border-bottom-style: hidden;
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#> padding-top: 8px;
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#> padding-left: 5px;
#> padding-right: 5px;
#> color: #333333;
#> background-color: #FFFFFF;
#> font-size: 80%;
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#> border-top-width: 2px;
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#>
#> #kkeulbfdpb .gt_empty_group_heading {
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#> border-top-style: solid;
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#> border-top-color: #D3D3D3;
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#> border-bottom-width: 2px;
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#> vertical-align: middle;
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#> margin-top: 0;
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#> margin-bottom: 0;
#> }
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#> padding-top: 7px;
#> padding-bottom: 7px;
#> padding-left: 5px;
#> padding-right: 5px;
#> margin: 10px;
#> border-top-style: solid;
#> border-top-width: 1px;
#> border-top-color: #F6F7F7;
#> border-left-style: none;
#> border-left-width: 1px;
#> border-left-color: #D3D3D3;
#> border-right-style: none;
#> border-right-width: 1px;
#> border-right-color: #D3D3D3;
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#> overflow-x: hidden;
#> }
#>
#> #kkeulbfdpb .gt_stub {
#> color: #333333;
#> background-color: #FFFFFF;
#> font-size: 80%;
#> font-weight: bolder;
#> text-transform: uppercase;
#> border-right-style: solid;
#> border-right-width: 2px;
#> border-right-color: #D3D3D3;
#> padding-left: 5px;
#> padding-right: 5px;
#> }
#>
#> #kkeulbfdpb .gt_stub_row_group {
#> color: #333333;
#> background-color: #FFFFFF;
#> font-size: 100%;
#> font-weight: initial;
#> text-transform: inherit;
#> border-right-style: solid;
#> border-right-width: 2px;
#> border-right-color: #D3D3D3;
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#> padding-right: 5px;
#> vertical-align: top;
#> }
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#> border-top-width: 2px;
#> }
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#> #kkeulbfdpb .gt_summary_row {
#> color: #333333;
#> background-color: #FFFFFF;
#> text-transform: inherit;
#> padding-top: 8px;
#> padding-bottom: 8px;
#> padding-left: 5px;
#> padding-right: 5px;
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#> #kkeulbfdpb .gt_first_summary_row {
#> border-top-style: solid;
#> border-top-color: #D3D3D3;
#> }
#>
#> #kkeulbfdpb .gt_first_summary_row.thick {
#> border-top-width: 2px;
#> }
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#> <table class="gt_table" data-quarto-disable-processing="false" data-quarto-bootstrap="false">
#> <thead>
#> <tr class="gt_heading">
#> <td colspan="4" class="gt_heading gt_title gt_font_normal" style>.</td>
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#> <tr class="gt_heading">
#> <td colspan="4" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>250 rows x 4 cols</td>
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#> <tr class="gt_col_headings">
#> <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1" scope="col" id="type"></th>
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#> <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1" scope="col" id="value">Plot Overview</th>
#> <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" scope="col" id="n_missing">Missing</th>
#> </tr>
#> </thead>
#> <tbody class="gt_table_body">
#> <tr><td headers="type" class="gt_row gt_left"><svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:20px;width:20px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#4e79a7;overflow:visible;position:relative;"><path d="M40 48C26.7 48 16 58.7 16 72v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V72c0-13.3-10.7-24-24-24H40zM192 64c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zm0 160c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zm0 160c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zM16 232v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V232c0-13.3-10.7-24-24-24H40c-13.3 0-24 10.7-24 24zM40 368c-13.3 0-24 10.7-24 24v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V392c0-13.3-10.7-24-24-24H40z"/></svg></td>
#> <td headers="name" class="gt_row gt_left" style="font-weight: bold;"><div style='max-width: 150px;'>
#> <details style='font-weight: normal !important;'>
#> <summary style='font-weight: bold !important;'>Sex</summary>
#> Male and Female
#> </details></div></td>
#> <td headers="value" class="gt_row gt_center"><?xml version='1.0' encoding='UTF-8' ?><svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' width='141.73pt' height='34.02pt' viewBox='0 0 141.73 34.02'><g class='svglite'><defs> <style type='text/css'><![CDATA[ .svglite line, .svglite polyline, .svglite polygon, .svglite path, .svglite rect, .svglite circle { fill: none; stroke: #000000; stroke-linecap: round; stroke-linejoin: round; stroke-miterlimit: 10.00; } .svglite text { white-space: pre; } .svglite g.glyphgroup path { fill: inherit; stroke: none; } ]]></style></defs><rect width='100%' height='100%' style='stroke: none; fill: none;'/><defs> <clipPath id='cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg=='> <rect x='0.00' y='0.00' width='141.73' height='34.02' /> </clipPath></defs><g clip-path='url(#cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg==)'></g><defs> <clipPath id='cpMS4wMHwxNDAuNzR8Mi45OXwyMy42MQ=='> <rect x='1.00' y='2.99' width='139.74' height='20.62' /> </clipPath></defs><g clip-path='url(#cpMS4wMHwxNDAuNzR8Mi45OXwyMy42MQ==)'><rect x='72.83' y='3.93' width='67.91' height='18.75' style='stroke-width: 1.07; stroke: none; stroke-linecap: butt; stroke-linejoin: miter; fill: #DDEAF7;' /><rect x='1.00' y='3.93' width='71.83' height='18.75' style='stroke-width: 1.07; stroke: none; stroke-linecap: butt; stroke-linejoin: miter; fill: #3181BD;' /></g><g clip-path='url(#cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg==)'><text x='1.00' y='30.18' style='font-size: 8.00px; font-family: "Arial";' textLength='43.61px' lengthAdjust='spacingAndGlyphs'>2 categories</text></g></g></svg></td>
#> <td headers="n_missing" class="gt_row gt_right">0.4%</td></tr>
#> <tr><td headers="type" class="gt_row gt_left gt_striped"><svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:20px;width:20px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#4e79a7;overflow:visible;position:relative;"><path d="M40 48C26.7 48 16 58.7 16 72v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V72c0-13.3-10.7-24-24-24H40zM192 64c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zm0 160c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zm0 160c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zM16 232v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V232c0-13.3-10.7-24-24-24H40c-13.3 0-24 10.7-24 24zM40 368c-13.3 0-24 10.7-24 24v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V392c0-13.3-10.7-24-24-24H40z"/></svg></td>
#> <td headers="name" class="gt_row gt_left gt_striped" style="font-weight: bold;"><div style='max-width: 150px;'>
#> <details style='font-weight: normal !important;'>
#> <summary style='font-weight: bold !important;'>Grade</summary>
#> 3, 2 and 1
#> </details></div></td>
#> <td headers="value" class="gt_row gt_center gt_striped"><?xml version='1.0' encoding='UTF-8' ?><svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' width='141.73pt' height='34.02pt' viewBox='0 0 141.73 34.02'><g class='svglite'><defs> <style type='text/css'><![CDATA[ .svglite line, .svglite polyline, .svglite polygon, .svglite path, .svglite rect, .svglite circle { fill: none; stroke: #000000; stroke-linecap: round; stroke-linejoin: round; stroke-miterlimit: 10.00; } .svglite text { white-space: pre; } .svglite g.glyphgroup path { fill: inherit; stroke: none; } ]]></style></defs><rect width='100%' height='100%' style='stroke: none; fill: none;'/><defs> <clipPath id='cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg=='> <rect x='0.00' y='0.00' width='141.73' height='34.02' /> </clipPath></defs><g clip-path='url(#cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg==)'></g><defs> <clipPath id='cpMS4wMHwxNDAuNzR8Mi45OXwyMy42MQ=='> <rect x='1.00' y='2.99' width='139.74' height='20.62' /> </clipPath></defs><g clip-path='url(#cpMS4wMHwxNDAuNzR8Mi45OXwyMy42MQ==)'><rect x='99.21' y='3.93' width='41.53' height='18.75' style='stroke-width: 1.07; stroke: none; stroke-linecap: butt; stroke-linejoin: miter; fill: #DDEAF7;' /><rect x='56.56' y='3.93' width='42.65' height='18.75' style='stroke-width: 1.07; stroke: none; stroke-linecap: butt; stroke-linejoin: miter; fill: #91B4DA;' /><rect x='1.00' y='3.93' width='55.56' height='18.75' style='stroke-width: 1.07; stroke: none; stroke-linecap: butt; stroke-linejoin: miter; fill: #3181BD;' /></g><g clip-path='url(#cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg==)'><text x='1.00' y='30.18' style='font-size: 8.00px; font-family: "Arial";' textLength='43.61px' lengthAdjust='spacingAndGlyphs'>3 categories</text></g></g></svg></td>
#> <td headers="n_missing" class="gt_row gt_right gt_striped">0.4%</td></tr>
#> <tr><td headers="type" class="gt_row gt_left"><svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:20px;width:20px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#4e79a7;overflow:visible;position:relative;"><path d="M40 48C26.7 48 16 58.7 16 72v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V72c0-13.3-10.7-24-24-24H40zM192 64c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zm0 160c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zm0 160c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zM16 232v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V232c0-13.3-10.7-24-24-24H40c-13.3 0-24 10.7-24 24zM40 368c-13.3 0-24 10.7-24 24v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V392c0-13.3-10.7-24-24-24H40z"/></svg></td>
#> <td headers="name" class="gt_row gt_left" style="font-weight: bold;"><div style='max-width: 150px;'>
#> <details style='font-weight: normal !important;'>
#> <summary style='font-weight: bold !important;'>LVI</summary>
#> Absent and Present
#> </details></div></td>
#> <td headers="value" class="gt_row gt_center"><?xml version='1.0' encoding='UTF-8' ?><svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' width='141.73pt' height='34.02pt' viewBox='0 0 141.73 34.02'><g class='svglite'><defs> <style type='text/css'><![CDATA[ .svglite line, .svglite polyline, .svglite polygon, .svglite path, .svglite rect, .svglite circle { fill: none; stroke: #000000; stroke-linecap: round; stroke-linejoin: round; stroke-miterlimit: 10.00; } .svglite text { white-space: pre; } .svglite g.glyphgroup path { fill: inherit; stroke: none; } ]]></style></defs><rect width='100%' height='100%' style='stroke: none; fill: none;'/><defs> <clipPath id='cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg=='> <rect x='0.00' y='0.00' width='141.73' height='34.02' /> </clipPath></defs><g clip-path='url(#cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg==)'></g><defs> <clipPath id='cpMS4wMHwxNDAuNzR8Mi45OXwyMy42MQ=='> <rect x='1.00' y='2.99' width='139.74' height='20.62' /> </clipPath></defs><g clip-path='url(#cpMS4wMHwxNDAuNzR8Mi45OXwyMy42MQ==)'><rect x='81.25' y='3.93' width='59.49' height='18.75' style='stroke-width: 1.07; stroke: none; stroke-linecap: butt; stroke-linejoin: miter; fill: #DDEAF7;' /><rect x='1.00' y='3.93' width='80.25' height='18.75' style='stroke-width: 1.07; stroke: none; stroke-linecap: butt; stroke-linejoin: miter; fill: #3181BD;' /></g><g clip-path='url(#cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg==)'><text x='1.00' y='30.18' style='font-size: 8.00px; font-family: "Arial";' textLength='43.61px' lengthAdjust='spacingAndGlyphs'>2 categories</text></g></g></svg></td>
#> <td headers="n_missing" class="gt_row gt_right">0.4%</td></tr>
#> <tr><td headers="type" class="gt_row gt_left gt_striped"><svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:20px;width:20px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#4e79a7;overflow:visible;position:relative;"><path d="M40 48C26.7 48 16 58.7 16 72v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V72c0-13.3-10.7-24-24-24H40zM192 64c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zm0 160c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zm0 160c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zM16 232v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V232c0-13.3-10.7-24-24-24H40c-13.3 0-24 10.7-24 24zM40 368c-13.3 0-24 10.7-24 24v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V392c0-13.3-10.7-24-24-24H40z"/></svg></td>
#> <td headers="name" class="gt_row gt_left gt_striped" style="font-weight: bold;"><div style='max-width: 150px;'>
#> <details style='font-weight: normal !important;'>
#> <summary style='font-weight: bold !important;'>PNI</summary>
#> Absent and Present
#> </details></div></td>
#> <td headers="value" class="gt_row gt_center gt_striped"><?xml version='1.0' encoding='UTF-8' ?><svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' width='141.73pt' height='34.02pt' viewBox='0 0 141.73 34.02'><g class='svglite'><defs> <style type='text/css'><![CDATA[ .svglite line, .svglite polyline, .svglite polygon, .svglite path, .svglite rect, .svglite circle { fill: none; stroke: #000000; stroke-linecap: round; stroke-linejoin: round; stroke-miterlimit: 10.00; } .svglite text { white-space: pre; } .svglite g.glyphgroup path { fill: inherit; stroke: none; } ]]></style></defs><rect width='100%' height='100%' style='stroke: none; fill: none;'/><defs> <clipPath id='cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg=='> <rect x='0.00' y='0.00' width='141.73' height='34.02' /> </clipPath></defs><g clip-path='url(#cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg==)'></g><defs> <clipPath id='cpMS4wMHwxNDAuNzR8Mi45OXwyMy42MQ=='> <rect x='1.00' y='2.99' width='139.74' height='20.62' /> </clipPath></defs><g clip-path='url(#cpMS4wMHwxNDAuNzR8Mi45OXwyMy42MQ==)'><rect x='94.16' y='3.93' width='46.58' height='18.75' style='stroke-width: 1.07; stroke: none; stroke-linecap: butt; stroke-linejoin: miter; fill: #DDEAF7;' /><rect x='1.00' y='3.93' width='93.16' height='18.75' style='stroke-width: 1.07; stroke: none; stroke-linecap: butt; stroke-linejoin: miter; fill: #3181BD;' /></g><g clip-path='url(#cpMC4wMHwxNDEuNzN8MC4wMHwzNC4wMg==)'><text x='1.00' y='30.18' style='font-size: 8.00px; font-family: "Arial";' textLength='43.61px' lengthAdjust='spacingAndGlyphs'>2 categories</text></g></g></svg></td>
#> <td headers="n_missing" class="gt_row gt_right gt_striped">0.4%</td></tr>
#> </tbody>
#>
#>
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#>
#> SUMMARY OF CATEGORICAL VARIABLES
#>
#> character(0)
#>
#> Sex has 250 observations and 2 levels.
#> Female: n = 121, 48.6% of valid cases.
#> Male: n = 128, 51.4% of valid cases.
#> Missing values: 1.
#>
#> Grade has 250 observations and 3 levels.
#> 1: n = 74, 29.72% of valid cases.
#> 2: n = 76, 30.52% of valid cases.
#> 3: n = 99, 39.76% of valid cases.
#> Missing values: 1.
#>
#> LVI has 250 observations and 2 levels.
#> Absent: n = 143, 57% of valid cases.
#> Present: n = 106, 43% of valid cases.
#> Missing values: 1.
#>
#> PNI has 250 observations and 2 levels.
#> Absent: n = 166, 67% of valid cases.
#> Present: n = 83, 33% of valid cases.
#> Missing values: 1.
#>
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#>
#> <tr class="gt_heading">
#> <td colspan="4" class="gt_heading gt_title gt_font_normal" style>.
#>
#> <tr class="gt_heading">
#> <td colspan="4" class="gt_heading gt_subtitle gt_font_normal
#> gt_bottom_border" style>250 rows x 4 cols
#>
#> <tr class="gt_col_headings">
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#> rowspan="1" colspan="1" scope="col" id="type">
#> <th class="gt_col_heading gt_columns_bottom_border gt_left"
#> rowspan="1" colspan="1" scope="col" id="name">Column
#> <th class="gt_col_heading gt_columns_bottom_border gt_center"
#> rowspan="1" colspan="1" scope="col" id="value">Plot Overview
#> <th class="gt_col_heading gt_columns_bottom_border gt_right"
#> rowspan="1" colspan="1" scope="col" id="n_missing">Missing
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#> <details style='font-weight: normal !important;'>
#> <summary style='font-weight: bold !important;'>Sex
#> Male and Female
#>
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#> <td headers="n_missing" class="gt_row gt_right">0.4%
#> <td headers="type" class="gt_row gt_left gt_striped"><svg
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#> style="font-weight: bold;"><div style='max-width: 150px;'>
#> <details style='font-weight: normal !important;'>
#> <summary style='font-weight: bold !important;'>Grade
#> 3, 2 and 1
#>
#> <td headers="value" class="gt_row gt_center gt_striped"><?xml
#> version='1.0' encoding='UTF-8' ?><svg
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#> <summary style='font-weight: bold !important;'>LVI
#> Absent and Present
#>
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#> <summary style='font-weight: bold !important;'>PNI
#> Absent and Present
#>
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#> <td headers="n_missing" class="gt_row gt_right gt_striped">0.4%Phase 4: Advanced Quality Assessment
Benford’s Law Analysis
# Fraud detection using Benford's law
benford(
data = histopathology,
var = "MeasurementA"
)
#>
#> BENFORD ANALYSIS
#>
#> See
#> <a href = 'https://github.com/carloscinelli/benford.analysis'>Package
#> documentation for interpratation.
#>
#> Benford object:
#>
#> Data: var
#> Number of observations used = 135
#> Number of obs. for second order = 134
#> First digits analysed = 2
#>
#> Mantissa:
#>
#> Statistic Value
#> Mean 0.506
#> Var 0.108
#> Ex.Kurtosis -1.514
#> Skewness -0.037
#>
#>
#> The 5 largest deviations:
#>
#> digits absolute.diff
#> 1 52 4.88
#> 2 17 4.65
#> 3 66 4.12
#> 4 13 3.66
#> 5 16 3.55
#>
#> Stats:
#>
#> Pearson's Chi-squared test
#>
#> data: var
#> X-squared = 137.97, df = 89, p-value = 0.0006808
#>
#>
#> Mantissa Arc Test
#>
#> data: var
#> L2 = 0.058715, df = 2, p-value = 0.000361
#>
#> Mean Absolute Deviation (MAD): 0.008005873
#> MAD Conformity - Nigrini (2012): Nonconformity
#> Distortion Factor: NaN
#>
#> Remember: Real data will never conform perfectly to Benford's Law. You should not focus on p-values! MeasurementA
#> <num>
#> 1: 0.0176978
#> 2: 1.7391655
#> 3: 0.5256537
#> 4: 1.7557878
#> 5: 0.5239132
#> 6: 0.1729459
#> 7: 0.1769035
#> 8: 0.5289038
#> 9: 0.5236107
#> 10: 1.7691411
#> 11: 0.5241260
#> 12: 0.5263020
#> 13: 1.7349714
#> 14: 0.1749262
#> $xlog
#> [1] FALSE
#>
#> $ylog
#> [1] FALSE
#>
#> $adj
#> [1] 0.5
#>
#> $ann
#> [1] TRUE
#>
#> $ask
#> [1] FALSE
#>
#> $bg
#> [1] "transparent"
#>
#> $bty
#> [1] "o"
#>
#> $cex
#> [1] 0.66
#>
#> $cex.axis
#> [1] 1
#>
#> $cex.lab
#> [1] 1
#>
#> $cex.main
#> [1] 1.2
#>
#> $cex.sub
#> [1] 1
#>
#> $col
#> [1] "black"
#>
#> $col.axis
#> [1] "black"
#>
#> $col.lab
#> [1] "black"
#>
#> $col.main
#> [1] "black"
#>
#> $col.sub
#> [1] "black"
#>
#> $crt
#> [1] 0
#>
#> $err
#> [1] 0
#>
#> $family
#> [1] ""
#>
#> $fg
#> [1] "black"
#>
#> $fig
#> [1] 0.6666667 1.0000000 0.0000000 0.5000000
#>
#> $fin
#> [1] 8 6
#>
#> $font
#> [1] 1
#>
#> $font.axis
#> [1] 1
#>
#> $font.lab
#> [1] 1
#>
#> $font.main
#> [1] 2
#>
#> $font.sub
#> [1] 1
#>
#> $lab
#> [1] 5 5 7
#>
#> $las
#> [1] 0
#>
#> $lend
#> [1] "round"
#>
#> $lheight
#> [1] 1
#>
#> $ljoin
#> [1] "round"
#>
#> $lmitre
#> [1] 10
#>
#> $lty
#> [1] "solid"
#>
#> $lwd
#> [1] 1
#>
#> $mai
#> [1] 1.02 0.82 0.82 0.42
#>
#> $mar
#> [1] 5.1 4.1 4.1 2.1
#>
#> $mex
#> [1] 1
#>
#> $mfcol
#> [1] 1 1
#>
#> $mfg
#> [1] 1 1 1 1
#>
#> $mfrow
#> [1] 1 1
#>
#> $mgp
#> [1] 3 1 0
#>
#> $mkh
#> [1] 0.001
#>
#> $new
#> [1] TRUE
#>
#> $oma
#> [1] 0 0 0 0
#>
#> $omd
#> [1] 0 1 0 1
#>
#> $omi
#> [1] 0 0 0 0
#>
#> $pch
#> [1] 1
#>
#> $pin
#> [1] 6.76 4.16
#>
#> $plt
#> [1] 0.0775000 0.9225000 0.1533333 0.8466667
#>
#> $ps
#> [1] 12
#>
#> $pty
#> [1] "m"
#>
#> $smo
#> [1] 1
#>
#> $srt
#> [1] 0
#>
#> $tck
#> [1] NA
#>
#> $tcl
#> [1] -0.5
#>
#> $usr
#> [1] 0.568 1.432 0.568 1.432
#>
#> $xaxp
#> [1] 0 1 5
#>
#> $xaxs
#> [1] "r"
#>
#> $xaxt
#> [1] "s"
#>
#> $xpd
#> [1] FALSE
#>
#> $yaxp
#> [1] 0 1 5
#>
#> $yaxs
#> [1] "r"
#>
#> $yaxt
#> [1] "s"
#>
#> $ylbias
#> [1] 0.2Agreement Analysis
# Example agreement analysis (if rater variables exist)
# Note: This requires specific rater variables in the dataset
# agreement(
# data = histopathology,
# vars = c("Rater1", "Rater2")
# )
cat("Agreement analysis available - see agreement vignette for detailed examples")
#> Agreement analysis available - see agreement vignette for detailed examplesBest Practices Summary
Conclusion
Regular data quality assessment using these techniques ensures reliable and trustworthy clinical research results. For detailed function usage and advanced examples, consult the individual function vignettes.
Best Practices
- Perform quality assessment before any statistical analysis
- Document and investigate any quality issues found
- Establish quality thresholds appropriate for your research context
- Implement ongoing quality monitoring throughout data collection
- Use multiple quality assessment methods for comprehensive evaluation