Calculator Inputs
Use the fields below to estimate recruitment quality, quota progress, effective sample size, and a practical uncertainty range for nonprobability studies.
Example Data Table
| Scenario | Method | Population | Target | Achieved | Effective | Bias Risk |
|---|---|---|---|---|---|---|
| Urban customer intercept | Convenience | 10,000 | 400 | 425 | 287.4 | 61.2 |
| Quota balanced shopper panel | Quota | 8,500 | 500 | 480 | 371.1 | 43.8 |
| Expert clinician review | Purposive | 1,200 | 120 | 108 | 84.6 | 47.5 |
| Hard-to-reach network study | Snowball | 5,000 | 300 | 256 | 143.9 | 71.0 |
These example rows are illustrative and help readers understand how the diagnostic outputs may look across different nonprobability designs.
Formula Used
For snowball studies:
Reachable Pool = Seeds × (1 + r + r² + ... up to waves)For other methods:
Reachable Pool = Initial Contacts
Achieved Sample = Reachable Pool × Eligibility Rate × Response Rate × (1 − Dropout Rate)
Weight Effect = 1 + (Weight CV)²Combined Design Effect = Base Design Effect × Weight Effect
Effective Sample = Achieved Sample ÷ Combined Design Effect
SE = √[p(1-p) ÷ Effective Sample] × FPCMOE = z × SECI = p ± MOE
The calculator combines method penalty, low response, quota shortfall, weak segment matching, weighting variability, design effect, and dropout into a practical 0–100 score.
Important: nonprobability samples do not justify strict probability-based inference. These formulas provide practical diagnostics, not formal survey-theory guarantees.
How to Use This Calculator
- Choose the nonprobability method that best matches your fieldwork design.
- Enter the total population, your target sample, and initial contacts or seeds.
- Fill in eligibility, response, and dropout rates from your field experience.
- Optionally enter a manual achieved sample if collection is already finished.
- Set the estimated proportion, confidence level, design effect, and weight variability.
- Add segment match to reflect how closely the achieved cases follow planned quotas or profiles.
- Use referrals and waves when you are modeling snowball recruitment.
- Submit the form to see the results above the calculator, then export CSV or PDF files.
Frequently Asked Questions
1) What does this calculator estimate?
It estimates reachable pool, achieved cases, effective sample size, quota attainment, heuristic confidence limits, and a practical bias risk score for nonprobability studies.
2) Why is the margin of error called heuristic?
Because nonprobability samples lack random selection. The calculator uses effective sample size and standard proportion formulas only as a practical approximation.
3) When should I enter a manual achieved sample?
Enter it when data collection is complete or partly complete. That value overrides the estimated recruitment count and gives a more realistic result summary.
4) How does segment match affect results?
Segment match measures how closely the achieved sample reflects planned quotas or key profiles. Lower alignment raises the bias risk score.
5) What is weight coefficient of variation?
It measures how uneven the final case weights are. Larger variation increases weighting effect and reduces effective sample size.
6) Should I use referrals and waves for every method?
No. Those inputs mainly matter for snowball studies. For other methods, the calculator keeps the reachable pool equal to initial contacts.
7) Is a low bias risk score proof of representativeness?
No. A low score only suggests fewer warning signals within the entered assumptions. It does not replace random sampling or external validation.
8) What is a good use case for this tool?
It works well for internal dashboards, pilot studies, market research panels, clinic recruitment, expert interviews, and hard-to-reach population tracking.