Based on recent psychometric developments, this paper presents a conceptual and practical guide for estimating internal consistency reliabil-ity of measures obtained as item sum or mean. The internal consistency re-liability coefficient is presented as a by-product of the measurement model underlying the item responses. A three-step procedure is proposed for its estimation, including descriptive data analysis, test of relevant measure-ment models, and computation of internal consistency coefficient and its confidence interval. Provided formulas include: (a) Cronbach’s alpha and omega coefficients for unidimensional measures with quantitative item re-sponse scales, (b) coefficients ordinal omega, ordinal alpha and nonlinear reliability for unidimensional measures with dichotomic and ordinal items, (c) coefficients omega and omega hierarchical for essentially unidimension-al scales presenting method effects. The procedure is generalized to weighted sum measures, multidimensional scales, complex designs with multilevel and/or missing data and to scale development. Four illustrative numerical examples are fully explained and the data and the R syntax are provided.