Imputation
Imputation replaces missing values in a dataset, such as unrecorded trial costs or EQ-5D scores, with estimated values so every record can be analysed.
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.
A concept page is a published entry on the wiki. Some concepts also have a full encyclopaedia article. The Health Economics Ontology (HEO) holds every concept, including dictionary terms without an article, so it is larger than the list of published pages. The knowledge graph shows how concepts relate to each other.
Imputation replaces missing values in a dataset, such as unrecorded trial costs or EQ-5D scores, with estimated values so every record can be analysed.
Incidence is the number of new cases of a disease arising in a population at risk over a set period, used to size patient groups and set model event rates.
A measure comparing the incidence rate of an outcome between two groups, accounting for differences in total person-time at risk.
An assumption that, within the information used for a survival analysis, censoring does not convey additional information about a person’s unobserved event time.
An indirect comparison estimates, for HTA, how two treatments never trialled head to head compare, using each one's trials against a common comparator.
Indirect treatment comparison (ITC) is the umbrella term for methods, such as NMA or MAIC, that compare treatments no trial has tested head to head.
Individual patient data meta-analysis systematically obtains, checks, and jointly synthesises participant-level records from eligible studies to estimate effects and investigate variation across studies or patients.
Information bias is systematic error in the exposure, outcome or cost data of a health study, arising from how the data are measured, recalled or recorded.
An instrumental variable is a variable that changes treatment or exposure uptake while, under specified causal assumptions, being independent of potential outcomes and affecting the outcome only through that treatment or exposure.
Instrumental variable analysis is a causal estimation approach that uses variation in treatment or exposure induced by a qualifying instrument to estimate an effect under explicit identification and modelling assumptions.
Intention-to-treat analysis compares outcomes and costs by randomised group, whatever treatment was received, estimating the effect of offering treatment.
An interim analysis compares the arms of a clinical trial before it formally ends, to decide whether to stop it early for benefit, harm or futility.
Internal consistency reliability is how strongly the items in one health questionnaire scale agree with each other, usually measured by Cronbach's alpha.
The interquartile range (IQR) is the gap between the 25th and 75th percentiles, the spread of the middle half of data such as skewed patient costs.
Interrupted time series (ITS) is a quasi-experimental design tracking an outcome before and after a health policy to estimate changes in level and trend.
Interviewer bias is systematic error caused by how an interviewer asks questions or behaves, as in time trade-off or willingness-to-pay surveys.
The intraclass correlation (ICC) is the share of variance in a health outcome lying between patients or clusters, used to judge reliability and clustering.
The jackknife is a resampling method that recomputes an estimate, such as mean cost, leaving out each observation in turn to gauge bias and standard error.
An internal validation procedure that repeatedly fits a model on all but one of K data folds and evaluates it on the held-out fold.
K10 is the ten-item Kessler scale, a non-preference-based measure of psychological distress used in population surveys and mental health trials.