.png){kind=icon}
返回
Repeated-measures contrasts for multiple-pattern hypotheses
.png){kind=icon}
PRE
AI
DOI：10.1037/1082-989X.8.3.275.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Contrast analysis of repeated-measures data generally focuses on hypotheses when only I pattern of results is of theoretical interest. This article articulates a framework for contrast analysis in repeated-measures contexts in which researchers have hypotheses relevant to I potential pattern or multiple potential patterns of results. For example, a researcher might ask whether participants exhibit a pattern of (a) immediate symptom reduction or (b) delayed symptom reduction. Alternatively, the researcher might ask whether 2 or more groups exhibit 2 or more patterns to differing degrees. Building on the familiar logic and computational procedures for 1-pattern hypotheses, the authors present a contrast analysis framework that integrates analysis of 1-pattern and multiple-pattern hypotheses and accommodates 1 group or multiple groups of participants.
Keyword:
REPEATED-MEASURES DESIGNS
TESTS
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
