Bayesian Adaptive Design
A trial design using Bayesian statistics to formally update hypothesis probabilities as data accumulate, allowing pre-specified adaptive decisions such as early stopping.
Encyclopaedia
Explore comprehensive, evidence-informed explanations of key health economics concepts, including their development, application and relationships to other concepts. Published entries are validated through human expert review.
Bayesian Analysis
A general statistical approach combining prior beliefs with observed data to produce updated posterior beliefs, unlike classical frequentist methods.
Bayesian Meta-Analysis
An approach combining evidence across studies using Bayesian methods, formally incorporating prior information to produce a posterior effect estimate distribution.
Begg Test
A statistical test for detecting publication bias in a meta-analysis, based on the rank correlation between effect size and its variance.
Beta Level
The predetermined acceptable probability of failing to detect a true effect, with one minus beta defining a study's statistical power.
Between-Study Heterogeneity
The genuine variation in true treatment effects across the studies in a meta-analysis, beyond what chance alone would explain.
Between-Subject Variation
The variability in an outcome measure observed across different individuals in a study, unlike within-subject variation in a single person's repeated measurements.
Bias-Variance Tradeoff
The tension in statistical modelling between a model's systematic error, or bias, and its sensitivity to the specific sample used to fit it, or variance.
Binomial Distribution
A discrete probability distribution describing the number of successes in a fixed number of independent trials with the same success probability each.
Block Randomization
A randomisation technique assigning participants to groups in balanced blocks of a set size, keeping numbers roughly equal throughout enrolment.
Bootstrap Standard Error
An estimate of a parameter's statistical uncertainty, calculated as the standard deviation of its value across many resampled datasets via bootstrapping.
Bootstrapping
A resampling technique estimating a statistic's sampling distribution by repeatedly drawing random samples, with replacement, from the original observed data.
Bootstrapping Method
The specific procedure of repeatedly resampling, with replacement, from a dataset to empirically approximate the sampling distribution of a statistic of interest.
Brier Score
A measure of probabilistic prediction accuracy, the mean squared difference between predicted probabilities and actual observed binary outcomes, lower being better.
C-Statistic
A measure of predictive discrimination equivalent to the area under the ROC curve, the probability of correctly ranking a random pair of individuals.
Case-Control Design
An observational design comparing individuals who have experienced an outcome, the cases, against similar individuals who have not, the controls, on prior exposure.
Causal Inference
The statistical and epistemological methods used to determine whether an observed association between an exposure and outcome reflects a genuine causal relationship.
Central Limit Theorem
A statistical theorem stating that the sample mean of enough independent, identically distributed variables approximates a normal distribution regardless of the underlying shape.
Chi-Square Distribution
A continuous probability distribution arising from the sum of squared standard normal variables, underlying tests such as goodness of fit.
Cluster Analysis
A statistical technique grouping individuals into subsets, called clusters, so members within a cluster are more similar to each other than to outsiders.