<form id="cp_calculatedfieldsf_pform_1">
Clinical Trial Size Calculator
Enter any 3 values to calculate the missing variable
<label for="fieldname1">Sample Size</label>
<input type="number" id="fieldname1" style="width: 100%;">
<label for="fieldname2">Z-value</label>
<input type="number" id="fieldname2" style="width: 100%;">
<label for="fieldname3">Expected Proportion (p)</label>
<input type="number" id="fieldname3" style="width: 100%;">
<label for="fieldname4">Margin of Error (E)</label>
<input type="number" id="fieldname4" style="width: 100%;">
<button type="button" onclick="calculate()" style="background-color: #0093da; color: white; width: 49%;">Calculate</button>
<button type="button" onclick="resetFields()" style="background-color: #0093da; color: white; width: 49%;">Reset</button>
<script>
function calculate()
const sampleSize = parseFloat(document.getElementById("fieldname1").value);
const zValue = parseFloat(document.getElementById("fieldname2").value);
const proportion = parseFloat(document.getElementById("fieldname3").value);
const marginError = parseFloat(document.getElementById("fieldname4").value);
if (isNaN(sampleSize) && !isNaN(zValue) && !isNaN(proportion) && !isNaN(marginError))
document.getElementById("fieldname1").value = (Math.pow(zValue, 2) * proportion * (1 - proportion)) / Math.pow(marginError, 2);
else if (!isNaN(sampleSize) && isNaN(zValue) && !isNaN(proportion) && !isNaN(marginError))
document.getElementById("fieldname2").value = Math.sqrt((sampleSize * Math.pow(marginError, 2)) / (proportion * (1 - proportion)));
else if (!isNaN(sampleSize) && !isNaN(zValue) && isNaN(proportion) && !isNaN(marginError))
document.getElementById("fieldname3").value = (sampleSize * Math.pow(marginError, 2)) / (Math.pow(zValue, 2) * (1 - proportion));
else if (!isNaN(sampleSize) && !isNaN(zValue) && !isNaN(proportion) && isNaN(marginError))
document.getElementById("fieldname4").value = Math.sqrt((Math.pow(zValue, 2) * proportion * (1 - proportion)) / sampleSize);
else
alert("Please leave one field empty to calculate its value.");
function resetFields()
document.getElementById("fieldname1").value =
;
document.getElementById("fieldname2").value = ;
document.getElementById("fieldname3").value =
;
document.getElementById("fieldname4").value = ;
</script>
</form>
Enter the sample size, Z-value, expected proportion, and margin of error into the calculator to determine the missing variable for a clinical trial.
Clinical Trial Size Formula
The following formula is used to calculate the sample size for a clinical trial given the Z-value, expected proportion, and margin of error.
n = (Z^2 * p * (1 - p)) / E^2
- n is the sample size
- Z is the Z-value (standard score)
- p is the expected proportion
- E is the margin of error
To calculate the sample size, multiply the square of the Z-value by the expected proportion and its complement (1 – p). Divide chat Calculator by the square of the margin of error.
What is a Clinical Trial?
A clinical trial is a research study conducted to evaluate the effectiveness and safety of medical, surgical, or behavioral interventions. These trials are the primary way researchers find out if a new treatment, like a new drug or diet or medical device (for example, a pacemaker), is safe and effective in people. Often, a clinical trial is used to learn if a new treatment is more effective and/or has less harmful side effects than the standard treatment.
How to Calculate Clinical Trial Size?
The following steps outline how to calculate the sample size for a clinical trial.
- First, determine the Z-value based on the desired confidence level.
- Next, determine the expected proportion (p) of the population.
- Next, determine the margin of error (E) you are willing to accept.
- Finally, calculate the sample size using the formula n = (Z^2 * p * (1 – p)) / E^2.
- After inserting the values and calculating the result, check your answer with the calculator above.
Example Problem :
Use the following variables as an example problem to test your knowledge.
Z-value = 1.96 (for a 95% confidence level)
Expected Proportion (p) = 0.5
Margin of Error (E) = 0.05