Statistics: application guides

Plan a two-group study to rule out an unacceptable loss of effect, or to demonstrate equivalence within a prespecified margin.

Plan a parallel trial that randomizes groups such as clinics rather than individual participants, for a continuous outcome.

Plan the event count and recruitment needed for a two-arm time-to-event comparison.

Explore a trial with planned interim analyses and possible early stopping for efficacy or futility.

Simulate a two-stage trial that may increase its second-stage sample size using interim conditional power.

Evaluate success and futility rules for a single-arm trial with a binary response endpoint.

Generate an experimental run plan to study several factors together and reveal interactions.

Model curvature in a response and find promising settings within a studied factor range.

Compare a stable process’s variation with externally defined lower and upper specification limits.

Monitor observations in time order for signals inconsistent with a stable process.

Estimate associations between covariates and event hazards in right-censored follow-up data.

Fit a survival distribution and explore survival beyond the observed follow-up period.

Estimate the probability of a particular event when other events can prevent it from occurring.

Combine independent study effect estimates while inspecting their precision and between-study differences.

Explore whether prespecified study-level characteristics explain variation in study effects.

Compare outcomes among treated participants and similar untreated participants in observational data.

Estimate a treatment mean difference for a chosen target population using propensity-based weights.

Estimate the average treatment effect by combining propensity adjustment with outcome prediction.

Compare outcome changes before and after an intervention between treated and comparison groups.

Compare long-term costs and quality-adjusted life-years (QALYs) when people move among a small set of health states.

Explore individual trajectories and the simulation variability around a fixed state-transition model.

Assess how uncertainty in transition probabilities and state costs affects a cost-effectiveness comparison.

Identify which individual model inputs most influence incremental net monetary benefit over a chosen range.

Compare choices with a finite sequence of chance outcomes and terminal costs and QALYs.

Estimate annual spending changes when an intervention replaces part of an existing treatment mix.

Explore how resource capacity affects queues, throughput and waiting in a service pathway.

Estimate regression relationships and predictive uncertainty using explicit priors and posterior sampling.

Model continuous outcomes nested within groups while sharing information across those groups.

Summarize single-dose exposure without fitting a full compartmental concentration model.

Evaluate equivalence of a positive exposure endpoint between test and reference formulations in a balanced crossover.

Fit a simple concentration–time curve after a single intravenous bolus and estimate compartment parameters.

Describe a direct saturating relationship between concentration and pharmacodynamic response.