Statistical Inferences on Mean Vectors and Linear Models

2006 ◽  
pp. 77-110
Keyword(s):  
Linear Models ◽  
Statistical Inferences ◽  
Mean Vectors

scholarly journals A Two-Sample Test for Mean Vectors in High-Dimensional Data

2017 ◽  
Vol 1 (2) ◽  
pp. 118
Author(s):  
Knavoot Jiamwattanapong ◽  
Samruam Chongcharoen
Keyword(s):  
Sample Size ◽  
High Dimensional Data ◽  
Null Distribution ◽  
High Dimensional ◽  
Measurement Technology ◽  
Test Statistic ◽  
Dna Microarray Data ◽  
Statistical Inferences ◽  
Sample Test ◽  
Mean Vectors

<p><em>Modern measurement technology has enabled the capture of high-dimensional data by researchers and statisticians and classical statistical inferences, such as </em><em>the renowned Hotelling’s T<sup>2</sup> test, are no longer valid when the dimension of the data equals or exceeds the sample size. Importantly, when correlations among variables in a dataset exist, taking them into account in the analysis method would provide more accurate conclusions. In this article, we consider the hypothesis testing problem for two mean vectors in high-dimensional data with an underlying normality assumption. A new test is proposed based on the idea of keeping more information from the sample covariances. The asymptotic null distribution of the test statistic is derived. The simulation results show that the proposed test performs well comparing with other competing tests and becomes more powerful when the dimension increases for a given sample size. The proposed test is also illustrated with an analysis of DNA microarray data. </em></p>

A Note on Effects of Digital Approximation in Linear Models

1974 ◽  
Vol 3 (9) ◽  
pp. 893-897
Author(s):  
Gerald McWilliams ◽  
James Poirot†
Keyword(s):  
Linear Models

Effects of Momentary Affect on Satisfaction Judgments

2020 ◽  
Vol 41 (2) ◽  
pp. 61-67
Author(s):  
Marko Tončić ◽  
Petra Anić
Keyword(s):  
Linear Models ◽  
Time Frame ◽  
Hierarchical Linear Models ◽  
Curvilinear Relationship ◽  
Positive And Negative Affect ◽  
Transient Events ◽  
Time Frames ◽  
Events Data ◽  
Level Satisfaction ◽  
Source Of Information

Abstract. This study aims to examine the effect of affect on satisfaction, both at the between- and the within-person level for momentary assessments. Affect is regarded as an important source of information for life satisfaction judgments. This affective effect on satisfaction is well established at the dispositional level, while at the within-person level it is heavily under-researched. This is true especially for momentary assessments. In this experience sampling study both mood and satisfaction scales were administered five times a day for 7 days via hand-held devices ( N = 74 with 2,122 assessments). Several hierarchical linear models were fitted to the data. Even though the amount of between-person variance was relatively low, both positive and negative affect had substantial effects on momentary satisfaction on the between- and the within-person level as well. The within-person effects of affect on satisfaction appear to be more pronounced than the between-person ones. At the momentary level, the amount of between-person variance is lower than in studies with longer time-frames. The affect-related effects on satisfaction possibly have a curvilinear relationship with the time-frame used, increasing in intensity up to a point and then decreasing again. Such a relationship suggests that, at the momentary level, satisfaction might behave in a more stochastic manner, allowing for transient events/data which are not necessarily affect-related to affect it.

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