重复测量和 MANOVA
方差分析、重复测量建模以及多响应数据的多重比较
重复测量模型是一种回归模型，其中观测值具有多个响应变量。多元方差分析 (MANOVA) 是一种统计方法，用于确定响应数据的向量在统计上是否不同。重复测量模型和 MANOVA 通常用于交叉和纵向研究，响应变量通常对应于在不同时间的测量值。Statistics and Machine Learning Toolbox™ 提供了适用于重复测量模型的各种函数，可用于执行单因素、双因素和 N 因素多元方差分析 (MANOVA)；方差分析 (ANOVA)；协方差分析 (ANCOVA)；以及创建 RepeatedMeasures 模型对象。
函数
对象
主题
重复测量
- Model Specification for Repeated Measures Models
Learn how to specify a repeated measures model infitrm. - Mauchly’s Test of Sphericity
Learn the test of sphericity used in repeated measures models. - Compound Symmetry Assumption and Epsilon Corrections
Learn the different epsilon corrections used in p-value calculations in the repeated measures ANOVA when the compound symmetry assumption fails. - Multivariate Analysis of Variance for Repeated Measures
Learn the four different methods used in multivariate analysis of variance for repeated measures models. - Wilkinson Notation
Wilkinson notation provides a way to describe regression and repeated measures models without specifying coefficient values.
MANOVA
- Perform Multivariate Analysis of Variance (MANOVA)
MANOVA is a form of ANOVA with multiple response variables. It determines whether the entire set of means is different from one group to the next.
