Psycholinguistic data are often analyzed with repeated-measures analyses of variance (ANOVA), but this paper argues that mixed-effects (multilevel) models provide a better alternative method. First, models are discussed in which the two random factors of participants and items are crossed, and not nested. Traditional ANOVAs are compared against these crossed mixed-effects models, for simulated ...

Abstract Background Little attention has been paid to customising fatigue questionnaires for patients with Substance Use Disorders (SUDs). The present study aims validate and shorten the nine-item Fatigue Severity Scale (FSS-9) Visual Analogue (VAFS) use this population. Methods We used data from a nested cohort annual health assessments responses on FSS-9 VAFS. During period 2016–2020, 917 wer...

We have examined the protease susceptibility of aortic myosin, the thermal unfolding profiles of myosin rod and light meromyosin (LMM) and the solubility properties of the LMM fragments. Two major protease-susceptible sites were found, located at the head-rod junction and the heavy meromyosin (HMM)-LMM junction. Both tryptic and chymotryptic digestion of aortic myosin rod produced the LMM (80-8...

Abstract: This paper proposes a nonlinear model based predictive control (NMPC) algorithm for nonlinear systems by using multiple models approach. To have a less complexity model we expand each linear sub-model on an orthogonal Laguerre basis, the characteristic pole of which should be optimized. In this paper we propose a pole optimization algorithm based on the Gauss-Newton method and we use ...

BACKGROUND The timing of associations between common genetic variants and changes in growth patterns over childhood may provide insight into the development of obesity in later life. To address this question, it is important to define appropriate statistical models to allow for the detection of genetic effects influencing longitudinal childhood growth. METHODS AND RESULTS Children from The We...

We propose the semiparametric small area estimator under the partially linear model. Unlike the linear mixed models widely used in the small area estimation, which assume that the area effect is the random effect, we model the area effect as the unknown function of an area-indicative variable. We represent the nonparametric part for area effect using penalized splines, by which the estimation a...

ABSTRACT The linear mixing model (LMM) is a well-known and useful method for decomposing spectra in a hyperspectral image into the sum of their constituents, or endmembers. Mathematically, if the spectra are represented as n-dimensional vectors, then the LMM implies that the set of endmembers defines a basis or coordinate system for the set of spectra. Because the endmembers themselves are gene...

Speech process has benefited a great deal from the wavelet transforms. Wavelet packets decompose signals in to broader components using linear spectral bisecting. In this paper, mixtures of speech signals are decomposed using wavelet packets, the phase difference between the two mixtures are investigated in wavelet domain. In our method Laplacian Mixture Model (LMM) is defined. An Expectation M...