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Demographic Data Analysis
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Demographic data analysis involves examining the basic characteristics of patients or study participants. This includes variables such as age, gender, weight, ethnicity, and treatment groups. Demographic analysis is an essential step in clinical trials because it helps ensure that the study population is balanced and representative.
Demographic datasets are usually stored in the demographics domain, which contains one record per subject. This data is used to describe the overall study population and to compare characteristics across treatment groups.
# Example demographic dataset
demo_data <- data.frame(
patient_id = 1:8,
age = c(45, 52, 37, 60, 49, 55, 42, 63),
gender = c("M", "F", "M", "F", "M", "F", "F", "M"),
weight = c(70, 65, 80, 68, 75, 72, 60, 85),
treatment = c("Drug", "Drug", "Placebo", "Drug",
"Placebo", "Drug", "Placebo", "Drug")
)The first step is to inspect the structure and summary of the dataset.
str(demo_data)
summary(demo_data)Descriptive statistics are used to summarize demographic variables.
| Measure | Purpose | R Function |
|---|---|---|
| Average age | Mean age of participants | mean(demo_data$age) |
| Gender distribution | Count of participants by gender | table(demo_data$gender) |
| Average weight | Mean weight of participants | mean(demo_data$weight) |
| Treatment count | Participants per treatment group | table(demo_data$treatment) |
Group-wise analysis helps compare demographic characteristics between treatment groups.
library(dplyr)
demo_data %>%
group_by(treatment) %>%
summarise(
average_age = mean(age),
average_weight = mean(weight),
patient_count = n()
)Visualization can also be used to understand demographic distributions.
library(ggplot2)
# Age distribution
ggplot(demo_data, aes(x = age)) +
geom_histogram() +
theme_minimal()
# Gender distribution by treatment
ggplot(demo_data, aes(x = treatment, fill = gender)) +
geom_bar(position = "dodge") +
theme_minimal()Demographic data analysis provides an overview of the study population. It helps ensure balanced treatment groups and supports the interpretation of clinical trial results.
