.nrr-calculator-container {
max-width: 600px;
margin: 0 auto;
background: #ffffff;
padding: 25px;
border-radius: 12px;
box-shadow: 0 4px 15px rgba(0,0,0,0.1);
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Helvetica, Arial, sans-serif;
}
.nrr-form-group {
margin-bottom: 20px;
}
.nrr-label {
display: block;
margin-bottom: 8px;
font-weight: 600;
color: #333;
font-size: 16px;
}
.nrr-input {
width: 100%;
padding: 12px;
border: 1px solid #ddd;
border-radius: 6px;
font-size: 16px;
box-sizing: border-box;
transition: border-color 0.3s;
}
.nrr-input:focus {
border-color: #007bff;
outline: none;
}
.nrr-btn {
width: 100%;
padding: 14px;
background-color: #007bff;
color: white;
border: none;
border-radius: 6px;
font-size: 18px;
font-weight: 600;
cursor: pointer;
transition: background-color 0.2s;
}
.nrr-btn:hover {
background-color: #0056b3;
}
.nrr-result-box {
margin-top: 25px;
padding: 20px;
background-color: #f8f9fa;
border-radius: 8px;
border-left: 5px solid #007bff;
display: none;
}
.nrr-result-item {
display: flex;
justify-content: space-between;
margin-bottom: 10px;
padding-bottom: 10px;
border-bottom: 1px solid #eee;
}
.nrr-result-item:last-child {
border-bottom: none;
margin-bottom: 0;
padding-bottom: 0;
}
.nrr-result-label {
color: #555;
font-weight: 500;
}
.nrr-result-value {
font-weight: 700;
color: #222;
}
.nrr-highlight {
font-size: 1.2em;
color: #dc3545; /* Red for non-response usually signals an issue */
}
.nrr-highlight-green {
font-size: 1.1em;
color: #28a745;
}
@media (max-width: 480px) {
.nrr-calculator-container {
padding: 15px;
}
}
function calculateNonResponse() {
var totalSample = parseFloat(document.getElementById('totalSampleSize').value);
var totalResponses = parseFloat(document.getElementById('totalResponses').value);
var resultBox = document.getElementById('nrrResult');
// Input Validation
if (isNaN(totalSample) || isNaN(totalResponses)) {
alert("Please enter valid numbers for both fields.");
resultBox.style.display = 'none';
return;
}
if (totalSample totalSample) {
alert("Total Responses cannot be greater than the Total Sample Size.");
resultBox.style.display = 'none';
return;
}
if (totalResponses < 0) {
alert("Responses cannot be negative.");
resultBox.style.display = 'none';
return;
}
// Calculations
var nonRespondents = totalSample – totalResponses;
var nonResponseRate = (nonRespondents / totalSample) * 100;
var responseRate = (totalResponses / totalSample) * 100;
// Updating the DOM
document.getElementById('displayRate').innerText = nonResponseRate.toFixed(2) + "%";
document.getElementById('displayMissing').innerText = nonRespondents.toLocaleString();
document.getElementById('displayResponseRate').innerText = responseRate.toFixed(2) + "%";
resultBox.style.display = 'block';
}
Non-Response Rate Calculator
The total number of units/people invited to participate.
The number of completed surveys or successful contacts.
Non-Response Rate:
0%
Total Non-Respondents:
0
Response Rate:
0%
How to Calculate Non-Response Rate
In survey research, marketing analysis, and data collection, the Non-Response Rate is a critical metric that measures the percentage of eligible participants in a sample who did not complete the survey or respond to the outreach. A high non-response rate can introduce non-response bias, potentially skewing your data and making your findings less representative of the total population.
The Non-Response Rate Formula
The calculation is straightforward. It compares the number of people who did not respond to the total number of eligible people who were invited to participate.
Non-Response Rate (%) = ( (Total Sample Size – Total Responses) / Total Sample Size ) × 100
Alternatively, if you already know the number of non-respondents:
Non-Response Rate (%) = (Number of Non-Respondents / Total Sample Size) × 100
Example Calculation
Let's say you are conducting a customer satisfaction survey.
- You email the survey to 1,000 customers (Total Sample Size).
- You receive completed surveys from 650 customers (Total Responses).
First, find the number of non-respondents:
1,000 – 650 = 350 non-respondents
Next, divide by the total sample size:
350 / 1,000 = 0.35
Finally, multiply by 100 to get the percentage:
0.35 × 100 = 35% Non-Response Rate.
Why is Non-Response Rate Important?
- Data Validity: If the people who didn't respond share common characteristics (e.g., they are all unhappy customers), your data will be biased towards happy customers.
- Cost Efficiency: High non-response rates in paid panels or direct mail campaigns mean a higher cost per valid response.
- Statistical Power: A smaller number of responses reduces the sample size, which increases the margin of error in your results.
Types of Non-Response
- Unit Non-Response: The potential respondent does not participate in the survey at all.
- Item Non-Response: The respondent participates but skips specific questions (often sensitive ones like income or age). Note: The calculator above is designed for Unit Non-Response.
How to Lower Your Non-Response Rate
To improve data quality, consider these strategies:
- Keep it short: Long surveys have higher abandonment rates.
- Incentivize: Offering a small reward or discount can significantly boost participation.
- Follow up: Sending reminders to non-respondents is one of the most effective ways to increase response rates.
- Optimize timing: Send surveys when your audience is most likely to be available.