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医生使用情况研究中的统计交互作用。前景与陷阱。

Statistical interactions in studies of physician utilization. Promise and pitfalls.

作者信息

Ronis D L, Harrison K A

机构信息

University of Michigan Institute for Social Research, Ann Arbor, Michigan.

出版信息

Med Care. 1988 Apr;26(4):361-72. doi: 10.1097/00005650-198804000-00005.

Abstract

It has been suggested that use of interactive statistical models would greatly increase the proportion of variance accounted for by studies of physician utilization. The purpose of this paper is to evaluate and describe the benefits and pitfalls of using interactive statistical models of physician utilization. The paper presents Monte Carlo simulation data and real world data to determine how much more of the variance in physician utilization can be accounted for by interactive regression models. Results indicate that adding interaction terms is unlikely to produce large increases in variance accounted for. The usefulness of interactive models is particularly low when there is substantial measurement error in the predictor variables. Other advantages and disadvantages of interactive models are discussed, including 1) improved understanding, 2) inflation of alpha, 3) sensitivity to transformations and scale of measurement, and 4) confounding of interaction effects with nonlinear effects.

摘要

有人提出,使用交互式统计模型将大大提高医生使用情况研究所能解释的方差比例。本文的目的是评估和描述使用医生使用情况交互式统计模型的益处和陷阱。本文呈现了蒙特卡罗模拟数据和实际数据,以确定交互式回归模型能够多解释多少医生使用情况的方差。结果表明,添加交互项不太可能大幅提高可解释的方差。当预测变量存在大量测量误差时,交互式模型的用处特别低。本文还讨论了交互式模型的其他优缺点,包括1)理解的改善,2)α的膨胀,3)对变换和测量尺度的敏感性,以及4)交互效应与非线性效应的混淆。

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