estimand = parameter to be estimated --> te schatten parameter

an 'an estimand' is differentiated from 'an estimator' (een 'schatter' is wat anders dan een 'estimand' (te schatten parameter):

Schatten

Een categorie van methoden die de statistiek hanteert om informatie te verkrijgen, wordt gevormd door de schattingsmethoden.

Een onbekende parameter [estimand] van een populatie (of verdeling) wordt geschat door een uit de steekproef berekende grootheid, de schatting. Het voorschrift dat bepaalt hoe de schatting uit de steekproef moet worden berekend, wordt schatter genoemd.

https://nl.wikipedia.org/wiki/Schatten

Estimator

In statistics, an estimator [schatter] is a rule for calculating an estimate [schatting / geschatte waarde] of a given quantity based on observed data: thus the rule (the estimator [schatter]), the quantity of interest (the estimand) and its result (the estimate [schatting]) are distinguished.

https://en.wikipedia.org/wiki/Estimator

An “estimator,” is a function used to obtain, from a given data set, an ‘estimate’ or ‘estimated value’ on the estimand of interest.

https://patents.google.com/patent/US11386506B2/en

An "estimator" or "point estimate" is a statistic (that is, a function of the data) that is used to infer the value of an unknown parameter in a statistical model. A common way of phrasing it is "the estimator is the method selected to obtain an estimate of an unknown parameter". The parameter being estimated is sometimes called the estimand.

https://en.wikipedia.org/wiki/Estimator

Estimand: Parameter in the population which is to be estimated in a statistical analysis.

Estimator: A rule for calculating an estimate of a given quantity based on observed data.
- Function of the observations, i.e., how observations are put together

Estimation:
- The process of finding an estimate, or approximation, which is a value that is usable for some purpose even if input data may be incomplete, uncertain, or unstable (value derived from the best information available)

Rule (the estimator), its result (the estimate) and the quantity of interest (the estimand) are distinguished.

https://bookdown.org/paul/applied-causal-analysis/estimator....

In estimation theory of statistics, "statistic" or estimator refers to samples, whereas "parameter" or estimand refers to populations, where the samples are taken from. A statistic is a numerical characteristic of a sample that can be used as an estimate of the corresponding parameter, the numerical characteristic of the population from which the sample was drawn.

For example, the sample mean (estimator), denoted X, can be used as an estimate of the mean parameter (estimand), denoted μ, of the population from which the sample was drawn. Similarly, the sample variance (estimator), denoted S2, can be used to estimate the variance parameter (estimand), denoted σ2, of the population from which the sample was drawn.

https://en.wikipedia.org/wiki/Parameter

Randomized controlled trials (RCTs) are the gold standard for evaluation of the efficacy and safety of investigational interventions. If every patient in an RCT were to adhere to the randomized treatment, one could simply analyze the complete data to infer the treatment effect. However, intercurrent events (ICEs) including the use of concomitant medication for unsatisfactory efficacy, treatment discontinuation due to adverse events, or lack of efficacy may lead to interventions that deviate from the original treatment assignment. Therefore, defining the appropriate estimand (the appropriate parameter to be estimated) based on the primary objective of the study is critical prior to determining the statistical analysis method and analyzing the data.

https://pubmed.ncbi.nlm.nih.gov/33098267/