Docs/Which Calculator?

Which Calculator Should I Use?

A quick guide to choosing the right statistical tool for your experiment.

What Are You Trying to Do?

“I want to reduce my sample size using baseline data”

You have pre-experiment measurements (last week's revenue, baseline lab values, historical engagement) that correlate with your outcome. CUPED uses this to reduce variance by 25-50%, meaning you need fewer subjects.

A/B TestsPre-Post DesignsClinical Trials with Baseline
Use CUPED Calculator

“I want to plan interim analyses with early stopping rules”

You're planning a trial where you want to look at the data partway through and potentially stop early for efficacy or futility. GSD provides statistically rigorous stopping boundaries that control Type I error.

Phase III TrialsAdaptive DesignsDMC Planning
Use GSD Calculator

“I want to design a trial using Bayesian methods”

You want to incorporate historical data, use informative priors, or design a trial with Bayesian decision rules. The Bayesian Toolkit is a 5-step workflow that takes you from prior specification through sample size determination.

Single-Arm Phase IIHistorical BorrowingRare DiseasesPediatric Extrapolation
Use Bayesian Toolkit

The 5-step workflow:

1. Prior Elicitation
2. Bayesian Borrowing
3. Sample Size
4. Two-Arm Design
5. Predictive Power

“I want to evaluate whether to continue at an interim”

You're at an interim analysis and want to know the probability that the trial will succeed if you continue. Bayesian PPoS gives you a direct probability to inform Go/No-Go decisions.

Interim FutilityGo/No-Go DecisionsPhase II/III Transition
Use Predictive Power Calculator

Note: If you're designing a new trial (not just evaluating an interim), start with the Bayesian Toolkit Overview to understand the full workflow.

Quick Comparison

I want to...Use ThisKey Output
Reduce sample size using baseline dataCUPEDAdjusted sample size, variance reduction %
Plan interim analyses with early stoppingGSDStopping boundaries, expected sample size
Design a trial with informative priorsBayesian ToolkitPrior specification, sample size, operating characteristics
Incorporate historical control dataBayesian BorrowingEffective prior, sample size reduction
Size a single-arm Bayesian trialBayesian Sample SizeN with Type I error and power
Size a two-arm Bayesian RCTTwo-Arm BayesianN per arm, allocation ratio impact
Evaluate trial success probability at interimPredictive PowerPPoS (%), Go/No-Go recommendation
All of the above for a complex trialSee belowCombined approach

Combining Calculators

For sophisticated trial designs, these tools complement each other:

1

Start with GSD for the overall design

Plan your interim analysis schedule and stopping boundaries. This gives you your maximum sample size and expected sample size under various scenarios.

2

Add CUPED for variance reduction

If you have baseline covariates, calculate how much smaller your trial can be. Apply the reduction to your GSD sample size.

3

Use Bayesian PPoS for internal Go/No-Go

At each interim, use PPoS to inform your decision to continue. GSD boundaries handle regulatory stopping; Bayesian informs internal strategy.

4

For Bayesian trial designs, follow the 5-step workflow

If using Bayesian methods for primary analysis (not just interim monitoring), start with Prior Elicitation and work through the toolkit sequentially.

Common Scenarios

ScenarioDescriptionCalculator(s)Approach
Tech A/B TestTesting a new feature on user engagementCUPEDUse last week's engagement as baseline
Phase III Clinical TrialPivotal trial with planned interim analysesGSD + Bayesian PPoSGSD for boundaries, Bayesian for futility
Phase II Proof-of-ConceptSingle-arm or small RCT with Go/No-Go gateBayesian ToolkitPrior → Sample Size → PPoS for decision
Single-Arm with Historical BorrowingPhase II using external control dataBayesian ToolkitPrior → Borrowing → Sample Size → PPoS
Rare Disease TrialSmall population, strong historical dataBayesian ToolkitMAP prior with aggressive borrowing
Pediatric ExtrapolationLeveraging adult trial dataBayesian BorrowingPower prior with appropriate discount
Long-Term Outcomes Study5-year follow-up with event-driven endpointsGSDO'Brien-Fleming boundaries

Decision Tree

What's your primary goal?
│
├─ Reduce sample size with baseline data
│  └─ → CUPED
│
├─ Plan frequentist interim stopping rules
│  └─ → GSD
│
├─ Design a new Bayesian trial
│  │
│  ├─ Do you have historical data to borrow?
│  │  ├─ YES → Bayesian Toolkit (Prior → Borrowing → Sample Size)
│  │  └─ NO  → Bayesian Toolkit (Prior → Sample Size)
│  │
│  └─ Single-arm or two-arm?
│     ├─ Single-arm → Bayesian Sample Size calculator
│     └─ Two-arm    → Two-Arm Bayesian Design calculator
│
└─ Evaluate an ongoing trial at interim
   └─ → Predictive Power (PPoS)