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Synthesizing Single-Case Experimental Designs: Modeling Complex Data Structures

delete2025-10-01
delete0
PRE
AI
K
Ke Cheng
Z
Zhiyao Yi
M
Mariola Moeyaert
S
S. Natasha Beretvas
W
Wim Van Den Noortgate
J
John M. Ferron *
DOI：10.1007/s10864-025-09602-xdelete
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摘要

摘要

En 中文
将多层模型应用于分析多个单被试研究的数据，可能导致在选择和估计适当模型方面面临挑战。过于复杂的模型可能无法得到良好估计，而过于简单的模型可能导致效应估计及其标准误差产生偏差。研究者旨在选择一个既能回答其研究问题、又足够简单以得到良好估计的模型，同时复杂到使效应估计几乎无偏、推断准确。这项蒙特卡洛模拟研究评估了使用不同复杂程度的混合线性模型来近似在个体内和跨个体间变化的非线性过程所带来的后果。我们发现，用两条线性分段对治疗阶段数据进行建模，所产生的治疗效应估计偏差更小、推断更准确，优于用二次轨迹对治疗阶段进行建模；并且，估计更复杂的异质方差结构，比假设简单方差结构能获得更准确的置信区间。
Keyword:
Single-case design
Multiple-baseline
Multilevel models
Non-linear models

期刊

J
Journal of Behavioral Education
IF:
1.2
论文数:
34
被引数:
1.1K

机构

U
University of South Florida
学者数:
526
论文数: 305
被引数: 2.1W
T
temple university
学者数:
447
论文数: 282
被引数: 0
S
state university of new york (suny) system
学者数:
6.5W
论文数: 5.8W
被引数: 65
P
pennsylvania commonwealth system of higher education (pcshe)
学者数:
12.9W
论文数: 11.7W
被引数: 177
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