# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "missalpha" in publications use:' type: software license: MIT title: 'missalpha: Find Range of Cronbach Alpha with a Dataset Including Missing Data' version: 0.2.0 doi: 10.32614/CRAN.package.missalpha abstract: Provides functions to calculate the minimum and maximum possible values of Cronbach's alpha when item-level missing data are present. Cronbach's alpha (Cronbach, 1951 ) is one of the most widely used measures of internal consistency in the social, behavioral, and medical sciences (Bland & Altman, 1997 ; Tavakol & Dennick, 2011 ). However, conventional implementations assume complete data, and listwise deletion is often applied when missingness occurs, which can lead to biased or overly optimistic reliability estimates (Enders, 2003 ). This package implements computational strategies including enumeration, Monte Carlo sampling, and optimization algorithms (e.g., Genetic Algorithm, Differential Evolution, Sequential Least Squares Programming) to obtain sharp lower and upper bounds of Cronbach's alpha under arbitrary missing data patterns. The approach is motivated by Manski's partial identification framework and pessimistic bounding ideas from optimization literature. authors: - family-names: Ji given-names: Feng email: f.ji@utoronto.ca - family-names: Zhou given-names: Biying email: biying.zhou@psu.edu repository: https://cran.r-universe.dev commit: 02d76680e8ff0b0ce98326dc3aee39013308fb58 date-released: '2025-10-29' contact: - family-names: Zhou given-names: Biying email: biying.zhou@psu.edu