Psychometric problems and issues involved with creating and using ipsative measures for selection
本文讨论了员工选拔中最常见的自比数据（强制选择自比数据）的心理测量特性，并通过求职者数据展示了自比与常模测量在相关模式和选拔决策上的显著差异。
Data are described as ipsative if a given set of responses always sum to the same total. However, there are many properties of data collection that can give rise to different types of ipsative data. In this study, the most common type of ipsative data used in employee selection (forced‐choice ipsative data; FCID) is discussed as a special case of other types of ipsative data. Although all ipsative data contains constraints on covariance matrices (covariance‐level interdependence), FCID contains additional item‐level interdependencies as well. The psychological processes that give rise to FCID and the resultant psychometric properties are discussed. In addition, data from which both normative and ipsative responses were provided by job applicants illustrate very different patterns of correlations as well as very different selection decisions between normative, FCID and ipsatized measures.