Effect sizes can be misleading: is it time to change the way we measure change?
Effect sizes can be misleading: is it time to change the way we measure change?
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DOI：
10.1136/jnnp.2009.201392
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发表时间：
2010-09-01
影响因子：
11
通讯作者：
Thompson, Alan J.
中科院分区：
文献类型：
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作者：
Hobart, Jeremy C.;Cano, Stefan J.;Thompson, Alan J.
目的以前的比较，以检测变化的能力在Barthel指数（BI）和功能独立性测量运动量表（FIMm）暗示这两个规模是同样的反应时，使用传统的效应量统计检查。在临床上，这是违反直觉的，因为FIMm比BI更有可能检测到变化，并引起了对效应量统计作为评定量表反应性指标的有效性的担忧。要检查这些问题，在这项研究中，一个复杂的心理测量分析，Rasch测量BI和FIMm data.Methods BI和FIMm数据进行了检查，从976人在一个单一的神经康复单位。使用Rasch分析比较BI和FIMm在组比较水平的反应性（效应大小，相对效率，结果从区间测量值和有序分数的组水平分析表明，BI和FIMm具有相同的反应性（BI和FIMm效应量范围分别为-0.82至-1.12和-0.77至-1.05）。然而，个体水平分析表明，FIMm检测到的显著改善人数几乎是BI的两倍（50%，n=496 vs 31%，n=298），出院时记录的无变化人数较少（FIMm 4%，n=38; BI 12%，n=115）。发现这种差异具有统计学显著性（卡方（2）=273.81; p
Objectives Previous comparisons of the ability to detect change in the Barthel Index (BI) and Functional Independence Measure motor scale (FIMm) have implied these two scales are equally responsive when examined using traditional effect size statistics. Clinically, this is counterintuitive as the FIMm has greater potential to detect change than the BI and raises concerns about the validity of effect size statistics as indicators of rating scale responsiveness. To examine these concerns, in this study a sophisticated psychometric analysis was applied, Rasch measurement to BI and FIMm data.Methods BI and FIMm data were examined from 976 people at a single neurorehabilitation unit. Rasch analysis was used to compare the responsiveness of the BI and FIMm at the group comparison level ( effect sizes, relative efficiency, relative precision) and for each individual person in the sample by computing the significance of their change.Results Group level analyses from both interval measurements and ordinal scores implied the BI and FIMm had equivalent responsiveness ( BI and FIMm effect size ranges -0.82 to -1.12 and -0.77 to -1.05, respectively). However, individual person level analyses indicated that the FIMm detected significant improvement in almost twice as many people as the BI (50%, n=496 vs 31%, n=298), and recorded less people as unchanged on discharge ( FIMm 4%, n=38; BI 12%, n=115). This difference was found to be statistically significant (chi(2)=273.81; p