Statistical analyses in psycholinguistics are often done by two separate ANOVAs for repeated measures, over subjects and over items. Multi-level modeling (MLM), by contrast, combines all random factors, subjects and items and any others, into a single full analysis. This property alone makes multi-level modeling superior over conventional single-level ANOVA techniques. This paper explains the b...

Research about the effect of cooperative learning settings faces the challenge of dealing with hierarchical data where observations regarding the learners are not stochastically independent. Standard methods like ANOVAs cannot deal with such data adequately. The article introduces multilevel modelling (MLM) as a statistical approach adequate for nested data. MLM allows taking into account inter...

Pioneering in the metabolism of noncultivable mycobacteria , Gray ( 5), Hanks (6), and Hanks and Gray ( 8) searched systematically for s u bst ra te s as prospective e ne rgy sources for M. leprae (MI) and M. lepraemurium (Mlm). After several years of investigations , they concluded that MI and Mlm cannot derive energy from substrates which cultivable mycobacteria use as energy sources for grow...

This paper presents a new method for characterizing brain responses in both PET and fMRI data. The aim is to capture the correlations between the scans of an experiment and a set of external predictor variables that are thought to affect the scans, such as type, intensity, or shape of stimulus response. Its main feature is a Canonical Variates Analysis (CVA) of the estimated effects of the pred...

This paper presents a new method for characterizing brain responses in both PET and fMRI data. The aim is to capture the correlations between the scans of an experiment and a set of external predictor variables that are thought to affect the scans, such as type, intensity, or shape of stimulus response. Its main feature is a Canonical Variates Analysis (CVA) of the estimated effects of the pred...

This paper presents a new method for characterizing brain responses in both PET and fMRI data. The aim is to capture the correlations between the scans of an experiment and a set of external predictor variables that are thought to aaect the scans, such as type, intensity, or shape of stimulus response. Its main feature is a Canonical Variates Analysis (CVA) of the estimated eeects of the predic...

In this paper, we propose a method for multi-class pattern classification by combined use of Multinomial Logit Model (MLM) and K-nearest neighbor rule (KNN). Multinomial Logit Model (MLM) is one of the neural network models for multi-class pattern classification, and is supposed to be equal or better in class&cation performance than linear classification methods. K-NN is a simple but powerful n...

We refine an active-database application taxonomy, proposed by Stonebraker, to include monotonic log monitoring applications (MLM). MLMs are a subclass of hard rule systems where triggering events are restricted to monotonic relations. We develop a formal semantic model for the MLM class. We then prove the correctness of concurrency schemes for applications within the model. Our results demonst...

In communications theory, Nakagami distribution (NKD) is used to model scattered signals that reach a receiver from different paths. In order to use NKD to model a given set of data, we will have to estimate its parameters from the given data. Method of L-Moments (MLM) is being compared with Method of Moments (MOM) for estimating the parameters of NKD. In this study, we have derived its first t...