Total number of participants enrolled at the beginning.
Participants who left the study before completion.
Attrition Rate:0%
Retention Rate:0%
Final Sample Size ($N_{final}$):0
function calculateAttrition() {
var initialInput = document.getElementById('initialParticipants');
var dropoutsInput = document.getElementById('dropouts');
var errorDiv = document.getElementById('error-message');
var resultDiv = document.getElementById('result-area');
// Reset display
errorDiv.style.display = 'none';
resultDiv.style.display = 'none';
var initial = parseFloat(initialInput.value);
var dropouts = parseFloat(dropoutsInput.value);
// Validation
if (isNaN(initial) || isNaN(dropouts)) {
errorDiv.innerText = "Please enter valid numbers for both fields.";
errorDiv.style.display = 'block';
return;
}
if (initial <= 0) {
errorDiv.innerText = "Initial sample size must be greater than zero.";
errorDiv.style.display = 'block';
return;
}
if (dropouts initial) {
errorDiv.innerText = "Dropouts cannot exceed the initial sample size.";
errorDiv.style.display = 'block';
return;
}
// Logic
var attritionRate = (dropouts / initial) * 100;
var retentionRate = 100 – attritionRate;
var finalSample = initial – dropouts;
// Display logic
document.getElementById('attritionResult').innerText = attritionRate.toFixed(2) + "%";
document.getElementById('retentionResult').innerText = retentionRate.toFixed(2) + "%";
document.getElementById('finalSampleResult').innerText = finalSample;
resultDiv.style.display = 'block';
}
How to Calculate Attrition Rate in a Study
In academic research, clinical trials, and longitudinal studies, understanding participant dropout is crucial for maintaining the validity of your data. The attrition rate measures the percentage of participants who discontinue the study before it is completed. A high attrition rate can introduce bias, reduce statistical power, and threaten the internal validity of your findings.
The Attrition Rate Formula
The standard formula for calculating the attrition rate is relatively simple. It represents the number of dropouts as a proportion of the initial sample size.
Attrition Rate (%) = ( Number of Dropouts / Initial Sample Size ) × 100
Conversely, you can calculate the Retention Rate, which is the percentage of participants who remained in the study until the end:
Retention Rate (%) = 100 – Attrition Rate
Step-by-Step Calculation Example
Let's look at a practical example involving a clinical weight-loss intervention trial:
Step 1: Identify the Initial Sample Size ($N_{start}$). Let's say you enrolled 150 participants at the baseline.
Step 2: Count the Dropouts. By the end of the 6-month trial, 24 participants had withdrawn or were lost to follow-up.
In this example, the study has an attrition rate of 16% and a retention rate of 84%.
Why Tracking Attrition Matters
Calculating this metric is not just a mathematical exercise; it has significant implications for research integrity:
Attrition Bias: If the participants who leave the study are systematically different from those who stay (e.g., only the sickest patients drop out of a drug trial), the results will be skewed.
Sample Power: Studies are designed with a specific sample size to detect effects. If too many participants leave, the study may become "underpowered," making it impossible to statistically prove a hypothesis.
Resource Management: Understanding typical attrition rates helps researchers "over-recruit" at the beginning of future studies to ensure enough data points remain at the end.
Acceptable Attrition Rates
While 0% attrition is ideal, it is rarely achievable in human research. Acceptable rates vary by field and study duration. Generally, an attrition rate below 5% is considered insignificant, while rates usually between 5% and 20% are acceptable but require analysis to ensure no bias exists. Rates exceeding 20% often raise concerns about the study's validity.