AA wahid, journal mustansiriyah of sports science, 2023

In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending on the mean square error criteria in where the estimation methods that were used are (Generalized Least Squares, M Robust, and Laplace), and for different sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best metho

In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending

Background/Objectives: Nonsurgical periodontal treatment (NSPT) is the gold-standard technique for treating periodontitis. However, an individual’s susceptibility or the inadequate removal of subgingival biofilms could lead to unfavorable responses to NSPT. This study aimed to assess the potential of salivary and microbiological biomarkers in predicting the site-specific and whole-mouth outcomes of NSPT. Methods: A total of 68 periodontitis patients exhibiting 1111 periodontal pockets 4 to 6 mm in depth completed the active phase of periodontal treatment. Clinical periodontal parameters, saliva, and subgingival biofilm samples were collected from each patient at baseline and three months after NSPT. A quantitative PCR assay was us

Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param

Resistance spot welding (RSW) aluminum alloys has a major problem of inconsistent quality from weld to weld, because of the problems of the non-uniform oxide layer. The high resistivity of the oxide causes strong heat released which influence significantly on the electrode lifetime and the weld quality. Much effort has been devoted experimentally to the study of the sheet surface characteristics for as-received sheet and surface pretreatment sheet by pickling in NaOH and glassblasted with three thicknesses (0.6, 1.0, and 1.5 mm) of AA1050. Three different welding process parameters energy setup as a low, medium, and high were carried. Tensile-shear strength tests were performed to indicate the weld quality. Moreover, microhardness tests,

In some cases, researchers need to know the causal effect of the treatment in order to know the extent of the effect of the treatment on the sample in order to continue to give the treatment or stop the treatment because it is of no use. The local weighted least squares method was used to estimate the parameters of the fuzzy regression discontinuous model, and the local polynomial method was used to estimate the bandwidth. Data were generated with sample sizes (75,100,125,150 ) in repetition 1000. An experiment was conducted at the Innovation Institute for remedial lessons in 2021 for 72 students participating in the institute and data collection. Those who used the treatment had an increase in their score after

This study investigates the impact of nonsurgical periodontal treatment (NSPT) on oral health-related quality of life (OHRQoL) in patients with periodontitis stages (S)2 and S3, and the factors associated with the prediction of patient-reported outcomes. Periodontitis patients (n = 68) with moderately deep periodontal pockets were recruited. Responses to the Oral Health Impact Profile (OHIP)-14 questionnaire and clinical parameters including plaque index, bleeding on probing (BOP), probing pocket depth (PPD), and clinical attachment loss (CAL) were recorded. All patients received supra- and subgingival professional mechanical plaque removal. All clinical parameters and questionnaire responses were recorded again 3 months after NSPT.