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Mean imputation can be carried out within classes (i.e. categories such as gender), and can be expressed as ^ = ¯ where ^ is the imputed value for record and ¯ is the sample mean of respondent data within some class . This is a special case of generalized regression imputation:
Predictive mean matching (PMM) [1] is a widely used [2] statistical imputation method for missing values, first proposed by Donald B. Rubin in 1986 [3] and R. J. A. Little in 1988. [ 4 ] It aims to reduce the bias introduced in a dataset through imputation, by drawing real values sampled from the data. [ 5 ]
In survey research, the design effect is a number that shows how well a sample of people may represent a larger group of people for a specific measure of interest (such as the mean). This is important when the sample comes from a sampling method that is different than just picking people using a simple random sample .
Multiple imputation is not conducted in specific disciplines, as there is a lack of training or misconceptions about them. [15] Methods such as listwise deletion have been used to impute data but it has been found to introduce additional bias. [16] There is a beginner guide that provides a step-by-step instruction how to impute data. [17]
ITT analysis is intended to avoid various misleading artifacts that can arise in intervention research such as non-random attrition of participants from the study or crossover. ITT is also simpler than other forms of study design and analysis, because it does not require observation of compliance status for units assigned to different ...
The arithmetic mean of a population, or population mean, is often denoted μ. [2] The sample mean ¯ (the arithmetic mean of a sample of values drawn from the population) makes a good estimator of the population mean, as its expected value is equal to the population mean (that is, it is an unbiased estimator).
Imputation and Variance Estimation Software (IVEware) is a collection of routines written under various platforms and packaged to perform multiple imputations, variance estimation (or standard error) and, in general, draw inferences from incomplete data. It can also be used to perform analysis without any missing data.
Imputation (statistics), substitution of some value for missing data; Imputation (genetics), estimation of unmeasured genotypes; Theory of imputation, the theory that factor prices are determined by output prices; Imputation (game theory), a distribution that benefits each player who cooperates in a game