Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.

In this paper an atmometer apparatus were used in the greenhouses for estimating reference evapotranspiration values. Experimental work was conducted in the agriculture research center in the College of Agriculture-University of Baghdad west of the city of Baghdad. One atmometer was used in eggplant greenhouse and in cucumber greenhouse through the winter growing season 2013-2014. FAO Penman-Monteith equation was applied outside the greenhouse and used only 65% from the value of ET_o in the greenhouses for estimating the reference evapotranspiration in the greenhouse. Moreover, Penman-Monteith equation was applied in greenhouses for the evaluating the performance of the atmometer. The results show that the erro

Gumbel distribution was dealt with great care by researchers and statisticians. There are traditional methods to estimate two parameters of Gumbel distribution known as Maximum Likelihood, the Method of Moments and recently the method of re-sampling called (Jackknife). However, these methods suffer from some mathematical difficulties in solving them analytically. Accordingly, there are other non-traditional methods, like the principle of the nearest neighbors, used in computer science especially, artificial intelligence algorithms, including the genetic algorithm, the artificial neural network algorithm, and others that may to be classified as meta-heuristic methods. Moreover, this principle of nearest neighbors has useful statistical featu

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

The educational service industry is one of the most negatively affected industries by the spread of the COVID-19 pandemic. Government agencies have taken many measures to slow its spread, and then restrict movement and gatherings and stop recreational activities. Furthermore, the repercussions of the curfew had a significant impact due to the interruption in actual attendance for students and employees, and the severity of the Covid-19 crisis and its (economic, social, security, humanitarian and behavioral) effects on all societies and work sectors is no secret to anyone. Iraq, like other countries, was also affected by the negative impact of Covid-19 pandemic in all fields of institutional work, especially public fields, and specifically t

KE Sharquie, R Hayani, J Al-Rawi, A Noaimi, SH Radhy, CLINICAL AND EXPERIMENTAL RHEUMATOLOGY, 2010

Objective: To evaluate knowledge towards smoking and its relationship with lung cancer among members of
Baghdad Nursing College.
Methodology: The study comprised 100 affiliates from the College of Nursing/ University of Baghdad that
included students, teaching staff and employees. All data was collected through a structured questionnaire
prepared by the National Cancer Research Center which were answered during a scientific symposium
organized by the center on lung Cancer Awareness in March 2016.The data were analyzed by using the SPSS,
version 22
Results: The age of the respondents ranged from (19-64 years); 76% were females and only 4% were smokers.
The results showed that the mean score for the level of knowled

In this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th