We consider estimation in a semiparametric generalized linear model for clustered data using estimating equations. Our results apply to the case where the number of observations per cluster is Ž nite, whereas the number of clusters is large. The mean of the outcome variable Œ is of the form g4Œ5 D X‚C ˆ4T 5, where g4¢5 is a link function, X and T are covariates, ‚ is an unknown parameter vector...

Poor water sanitation and hygiene practice can be associated with increased morbidity mortality. The study aimed to determine the effectiveness of health education intervention using information, motivation a behavioural skill model on (WASH) among adolescent girls in Maiduguri Metropolitan Council, Borno State, Nigeria. A school-based cluster randomized control trial was conducted 417 (10 19 y...

We prove special decay properties of solutions to the initial value problem associated to the k-generalized Korteweg-de Vries equation. These are related with persistence properties of the solution flow in weighted Sobolev spaces and with sharp unique continuation properties of solutions to this equation. As application of our method we also obtain results concerning the decay behavior of pertu...

Although there have been many researches in cluster analysis to consider on feature weights, little effort is made on sample weights. Recently, Yu et al. (2011) considered a probability distribution over a data set to represent its sample weights and then proposed sample-weighted clustering algorithms. In this paper, we give a sample-weighted version of generalized fuzzy clustering regularizati...

Generalized estimating equations (GEE) are commonly used for the analysis of correlated data. However, use of quadratic inference functions (QIFs) is becoming popular because it increases efficiency relative to GEE when the working covariance structure is misspecified. Although shown to be advantageous in the literature, the impacts of covariates and imbalanced cluster sizes on the estimation p...

Fan, Heckman and Wand (1995) proposed locally weighted kernel polynomial regression methods for generalized linear models and quasilikelihood functions. When the covariate variables are missing at random, we propose a weighted estimator based on the inverse selection probability weights. Distribution theory is derived when the selection probabilities are estimated nonparametrically. We show tha...