Multilevel models are among the most important models widely used in the application and analysis of data that are characterized by the fact that observations take a hierarchical form, In our research we examined the multilevel logistic regression model (intercept random and slope random model) , here the importance of the research highlights that the usual regression models calculate the total variance of the model and its inability to read variance and variations between levels ,however in the case of multi-level regression models, the calculation of  the total variance is inaccurate and therefore these models calculate the variations for each level of the model, Where the research aims to estimate the parameters of this m

Abstract

   Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model

    In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe

Abstract

            Rayleigh distribution is one of the important distributions used for analysis life time data, and has applications in reliability study and physical interpretations. This paper introduces four different methods to estimate the scale parameter, and also estimate reliability function; these methods are Maximum Likelihood, and Bayes and Modified Bayes, and Minimax estimator under squared error loss function, for the scale and reliability function of the generalized Rayleigh distribution are obtained. The comparison is done through simulation procedure, t

The compound 2,2'-(((1H-benzo(d)imidazol-2-yl)methyl)azanediyl)bis(ethan-1-ol) was reacted with benzyl bromide to afford compound (1) which used as row material to prepare a series of compounds through condensation reaction, the starting compound were reacted with tosyl chloride to protect the OH group  to afford compound 2, then reacted benzyl bromide to produce compound (2), then the compound (2) treated with three compounds ( 2-mercaptobenzthiazole, 2-mercaptobenimidazol and 2-chloromethyl benzimidazole) to form compounds 3a,b, 4a,b and 5a,b respectively. In the another step the click reaction of compound 2,2'-(((1H-benzo(d)imidazol-2-yl)methyl)azanediyl)bis(ethan-1-ol) with Propargyl bromide produce compound  6  which reacted

Complexes of 1-phenyl-3-(2(-5-(phenyl amino)-1,3,4-thiadiazole-2-yl)phenyl) thiourea have been prepared and characteizedby elemental analysis, Ff-[R, and u.v./ visible spectra moreover,determination of metal content M%o by flame atomic absorptionspectroscopy, molar conductance in DMSO solution and magneticmoments (peffl.The result showed that the ligand (L) was coordinated to Mn+2, Ni+2,Ct+2,2n+2,Cd+2, and Hg+2 ions through the nitrogen atoms and sulpheratoms.From the result obtained, rhe following general formula [MLCl2] hasbeen given for the prepared complexes with an octahedral geometryaround the metal ions for all complexes.where M= Mn+2, Ni+2, cu+2, zn+2, cd+2, and Hg+2 l= l-phenyl-3-(2-(5-(phenyl amino

   This research includes the application of non-parametric methods in estimating the conditional survival function represented in a method (Turnbull) and (Generalization Turnbull's) using data for Interval censored of breast cancer and two types of treatment, Chemotherapy and radiation therapy and age is continuous variable, The algorithm of estimators was applied through using (MATLAB) and then the use average Mean Square Error (MSE) as amusement  to the estimates and the results showed (generalization of Turnbull's) In estimating the conditional survival function and for both treatments ,The estimated survival of the patients does not show very large differences

In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t