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【求助】单因素方差分析与重复测量方差分析的选择？
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实验设计：探讨认知刺激对步态的影响，并比较不同刺激对步态影响是否相同，15名老年人，让受试者自然步行，分别接受4种不同认知刺激条件下步行，（同一天完成5组测试，每次间隔5分钟），测量步频、步速、步幅。比较5组数据间差异是否具有统计学意义，并两两比较。我选择单因素方差分析，审稿人建议改用重复测量方差分析，自学了一下重复测量方差分析，仍然不是很理解，请各路大神指教！！！
不知道邀请谁？试试他们
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讲的很详细
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感谢！可以给个链接吗？
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你这是属于两因素多水平的重复测量设计，首先要进行协方差球形性检验，结果的解读有这么几个，不同时相之间步态有无差别；不同认知刺激与时相是否存在交互作用；不同认知刺激之间是否存在差别，
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你的数据有点多，测量的指标有3个，步频、步速、步幅，（这3个能否划某种划分成一个数据），有4种不同的刺激，有5个时间点。我有一个问题：是刺激了一下，开始测试，休息5min, 再测试。
如果是这种不同时间点比较就说明刺激后，不同时间比较还是刺激－－测试－－休息5min
－－刺激－－测试。
如果是这种，理论上不同时间点没差别，因为中间休息过。另外个问题，你研究的主要目的，难道不是比较4种不同的刺激吗
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大飞05 你的数据有点多，测量的指标有3个，步频、步速、步幅，（这3个能否划某种划分成一个数据），有4种不同的刺激，有5个时间点。我有一个问题：是刺激了一下，开始测试，休息5min, 再测试。
如果是这种不同时间点比较就说明刺激后，不同时间比较还是刺激－－测试－－休息5min
－－刺激－－测试。
如果是这种，理论上不同时间点没差别，因为中间休息过。另外个问题，你研究的主要目的，难道不是比较4种不同的刺激吗感谢！是第二种，请问应该如何做统计？最后结果怎么呈现？研究目的是比较刺激与不刺激的差异以及4中不同刺激是否存在差异！再次感谢大哥指教！
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李晓松主编的 医学统计学 原话：重复测量资料是同一受试对象的同一观察指标在不同时间点上进行多次测量所获得的资料，常用来分析该观察指标在不同时间点上的变化特点。我的观点是，你设计的目的，是重复测一下，可以增大样本量。各个时间点之间，不需要比较。简单点，是可以用单因素方差分析的。既然编辑让你用重复测量，你可以把你的资料列成重复测量资料，用spss做一下就好。 比较依然是不同刺激间的比较。具体操作，你找本有案例的教材，照着用SPSS做一遍就好了。
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4种刺激与空白组比较
dunnt-t检验4种刺激之间的22比较，SNK或LSD。这些大家都懂的
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附件异常、链接失效
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lujun001 edited on
两因素重复测量资料的方差分析
微信扫一扫
广告宣传推广
政治敏感、违法虚假信息
恶意灌水、重复发帖
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附件异常、链接失效
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