A Trifactor Model for Integrating Ratings Across Multiple Informants

被引:69
|
作者
Bauer, Daniel J. [1 ]
Howard, Andrea L. [1 ]
Baldasaro, Ruth E. [1 ]
Curran, Patrick J. [1 ]
Hussong, Andrea M. [1 ]
Chassin, Laurie [2 ]
Zucker, Robert A. [3 ]
机构
[1] Univ N Carolina, Dept Psychol, Chapel Hill, NC 27599 USA
[2] Arizona State Univ, Dept Psychol, Tempe, AZ 85287 USA
[3] Univ Michigan, Dept Psychol, Ann Arbor, MI 48109 USA
关键词
factor analysis; raters; informants; observers; sources; MULTITRAIT-MULTIMETHOD DATA; CONFIRMATORY FACTOR-ANALYSES; ITEM RESPONSE THEORY; OF-FIT INDEXES; PARENTAL RATINGS; BEHAVIOR PROBLEMS; MATERNAL RATINGS; CHILD-BEHAVIOR; BIFACTOR; RATER;
D O I
10.1037/a0032475
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Psychologists often obtain ratings for target individuals from multiple informants such as parents or peers. In this article we propose a trifactor model for multiple informant data that separates target-level variability from informant-level variability and item-level variability. By leveraging item-level data, the trifactor model allows for examination of a single trait rated on a single target. In contrast to many psychometric models developed for multitrait-multimethod data, the trifactor model is predominantly a measurement model. It is used to evaluate item quality in scale development, test hypotheses about sources of target variability (e.g., sources of trait differences) versus informant variability (e.g., sources of rater bias), and generate integrative scores that are purged of the subjective biases of single informants.
引用
收藏
页码:475 / 493
页数:19
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