Calculating Sample Size For Prospective Cohort Study

Sample Size Formula for Cohort Study:

\[ n = \frac{Z^2 (p_1(1-p_1) + p_2(1-p_2))}{(p_1 - p_2)^2} \]

Z-Score (Z):

Proportion 1 (p1):

Proportion 2 (p2):

Difference (p1 - p2):

Sample Size (n):

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1. What is Sample Size Calculation for Cohort Study?

Sample size calculation for prospective cohort studies determines the number of participants needed to detect a specified effect size with adequate statistical power. This ensures the study can reliably answer the research question.

2. How Does the Calculator Work?

The calculator uses the cohort study sample size formula:

\[ n = \frac{Z^2 (p_1(1-p_1) + p_2(1-p_2))}{(p_1 - p_2)^2} \]

Where:

\( n \) — Required sample size per group
\( Z \) — Z-score corresponding to desired confidence level
\( p_1 \) — Proportion in exposed group
\( p_2 \) — Proportion in unexposed group
\( p_1 - p_2 \) — Expected difference between proportions

Explanation: This formula calculates the minimum number of participants needed in each group to detect a specified difference in proportions with adequate statistical power.

3. Importance of Sample Size Calculation

Details: Proper sample size calculation is crucial for study validity. It ensures adequate power to detect meaningful effects, prevents wasted resources on underpowered studies, and helps in proper study planning and budgeting.

4. Using the Calculator

Tips: Enter Z-score (typically 1.96 for 95% confidence), expected proportions in both groups, and the expected difference between proportions. All values must be valid (proportions between 0-1, difference ≠ 0).

5. Frequently Asked Questions (FAQ)

Q1: What Z-score should I use?
A: For 95% confidence level, use Z=1.96; for 90% confidence, use Z=1.645; for 99% confidence, use Z=2.576.

Q2: How do I estimate the proportions?
A: Use previous studies, pilot data, or clinical expertise. p1 is the expected proportion in the exposed group, p2 in the unexposed group.

Q3: What if I need to account for dropouts?
A: Increase the calculated sample size by 10-20% to account for potential loss to follow-up in cohort studies.

Q4: Is this for one-sided or two-sided tests?
A: This formula is typically for two-sided tests. For one-sided tests, use different Z-scores corresponding to one-tailed probabilities.

Q5: What about unequal group sizes?
A: This formula assumes equal group sizes. For unequal allocation, additional adjustments are needed to the sample size calculation.