How Do Missing Data Bias Estimates of Within-Group Agreement? Sensitivity of SD WG , CV WG , r WG(J) , r WG(J) * , and ICC to Systematic Nonresponse
分析了随机和非随机缺失数据模式对组内一致性和可靠性指标（如标准差、变异系数、组内相关系数等）的偏差影响，发现常见应答率下偏差可达20%，并提供了校正公式以评估多水平结果对调查无应答的敏感性。
In multilevel theory testing, estimation of group-level properties (i.e., consensus and diversity) is often complicated by missing data. Researchers are left to draw inferences about group constructs (e.g., organizational climate and climate strength) from the responses of only a subset of group members. This study analyzes the biasing impact of random and non-random missingness patterns on within-group agreement and reliability (standard deviation, coefficient of variation, r WG(J) , r * WG(J) , AD M , a WG , and intraclass correlation) across a range of response rates, numbers of items, and systematic missing data mechanisms. Results demonstrate biases up to 20% over- or underestimation for common response rates found in organizational research. Correction formulae are presented, which enable assessment of the sensitivity of multilevel results to survey nonresponse.