The article discusses the debate over whether to use item parcels or individual items in factor analysis and structural equation modeling (SEM). It argues that the controversy is not necessary, as parcels are a valid analytic tool with advantages and limitations depending on the context. Parcels are not inherently inaccurate or faulty, but they can be useful when thoughtfully constructed to provide efficient, reliable, and valid indicators of latent constructs. The article highlights the importance of understanding the sources of variance in items, including construct variance, specific variance, and measurement error, when creating parcels. It also discusses the potential problems that can arise from ill-informed use of parcels and emphasizes the need for caution in their application. The article reviews the psychometric characteristics of parcels and the algebra that underlies them, as well as evidence supporting their use and caution under certain circumstances. It also discusses the different types of scale types, including parallel, tau-equivalent, and congeneric indicators, and how they affect the measurement of constructs. The article also addresses the issue of dimensionality, purity, and operational specificity of items, and how these factors influence the effectiveness of parcels. The article also discusses the covariance algebra of parcels, which shows how parceling can reduce nuisance parameters and sampling variability. It explains how parcels can be used to create indicators with better measurement properties by combining items to reduce unwanted variances. The article also addresses the issue of error sources, including sampling error and parsimony error, and how they can affect the accuracy of model estimates. The article concludes by summarizing the pro- and anti-parcel arguments, emphasizing that parcels can be useful in certain situations but should be used with caution. It also highlights the importance of understanding the underlying constructs and item-level relationships when using parcels to ensure accurate model estimates. The article suggests that parcels can be a valuable tool in SEM, but their use should be guided by a thorough understanding of the constructs and the data being analyzed.The article discusses the debate over whether to use item parcels or individual items in factor analysis and structural equation modeling (SEM). It argues that the controversy is not necessary, as parcels are a valid analytic tool with advantages and limitations depending on the context. Parcels are not inherently inaccurate or faulty, but they can be useful when thoughtfully constructed to provide efficient, reliable, and valid indicators of latent constructs. The article highlights the importance of understanding the sources of variance in items, including construct variance, specific variance, and measurement error, when creating parcels. It also discusses the potential problems that can arise from ill-informed use of parcels and emphasizes the need for caution in their application. The article reviews the psychometric characteristics of parcels and the algebra that underlies them, as well as evidence supporting their use and caution under certain circumstances. It also discusses the different types of scale types, including parallel, tau-equivalent, and congeneric indicators, and how they affect the measurement of constructs. The article also addresses the issue of dimensionality, purity, and operational specificity of items, and how these factors influence the effectiveness of parcels. The article also discusses the covariance algebra of parcels, which shows how parceling can reduce nuisance parameters and sampling variability. It explains how parcels can be used to create indicators with better measurement properties by combining items to reduce unwanted variances. The article also addresses the issue of error sources, including sampling error and parsimony error, and how they can affect the accuracy of model estimates. The article concludes by summarizing the pro- and anti-parcel arguments, emphasizing that parcels can be useful in certain situations but should be used with caution. It also highlights the importance of understanding the underlying constructs and item-level relationships when using parcels to ensure accurate model estimates. The article suggests that parcels can be a valuable tool in SEM, but their use should be guided by a thorough understanding of the constructs and the data being analyzed.