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Öğe Comparison Of Some Variance Component Estimation Methods With Respect to Type I Eror Rate(Univ Namik Kemal, 2012) Genc, S.; Mendes, M.; Kocabas, Z.; Soysal, M., IIn this study; Variance components and probability of Type I Error were estimated by Analysis of Variance (ANOVA), Maximum Likelihood (ML) and Restricted Maximum Likelihood (REML) when the assumptions of analysis of variance were violated. For this purpose, random numbers from equal and not equal variances Z (0,1), t (10), (3) chi(2), beta(5,2) distributions with the various sample sizes (n=5, 10, 20, 30, 40, 50) and group numbers (k=3, 4, 10) were generated by simulation technique. Depending on the findings of this study with 100000 simulation, it is concluded that probability of type I error (alpha) estimated by ANOVA and ML was not protected in small sample sizes (n=5, 10) even if assumption of analysis of variance were met. Whenever variance components were estimated by REML, probability of type I error protected as % 5. All methods (ANOVA, ML, REML) were affected when homogeneity was violated at this affect shows clearly by measured heterogeneity. When the group number (k=4,10) increased that was affect to change probability of type I error.Öğe EFFECT OF STOCKING DENSITY ON DEVIATION FROM BILATERAL SYMMETRY AND SLAUGHTER WEIGHT IN BROILERS(Pakistan Agricultural Scientists Forum, 2013) Mirtagioglu, H.; Mollaogullari, A.; Genc, S.; Mendes, M.The main objective of this study was to investigate the effect of two different stocking densities (11 birds / m(2) and 17 birds / m(2)) on deviation from bilateral symmetry in broiler chickens. For this purpose, the weekly body weight, left and right shank length, shank width, wing length, face width and face length of the same birds were measured on from 7th to 42nd days of age. Repeated measurements analysis of variance was used to investigate the effect of stocking densities and ages (week) on relative asymmetry. Binary logistic regression analysis was used to determine the most important morphological character influencing the deviation from ideal slaughter weight of 1800 g. The overall relative asymmetry mean for shank width was significantly greater in control group (2.42 +/- 0.41) than in treatment group (1.87 +/- 0.43). The results of binary logistic regression analysis showed that only increase in difference of width in left and right shank caused significant change (p= 0.0148) in slaughter weight. In this study, the deviation from the bilateral symmetry was mostly found in fluctuating asymmetry for the measured characters in treatment group (11 birds per m(2)), and the low fluctuating asymmetry level was generally indicated higher welfare level and lower developmental instability for this group than that of the control group (17 birds per m(2)). Stocking density can be stated as one of the most important environmental factors which may influence developmental stability, welfare and performance of broilers.Öğe INFLUENCE OF USING ALTERNATIVE MEANS ON TYPE-I ERROR RATE IN THE COMPARISON OF INDEPENDENT GROUPS(Pakistan Agricultural Scientists Forum, 2014) Mirtagioglu, H.; Yigit, S.; Mollaogullari, A.; Genc, S.; Mendes, M.In this study, the effect of using trimmed, winsorized, and modified means instead of arithmetic mean on type-I error rate was investigated when the assumptions of the one-way ANOVA were not satisfied. Therefore, random numbers were generated by simulation technique from the populations distributed by Normal (0,1), Beta (5,2) and chi(2) (3) for 3 and 4 groups. The results of 30 000 simulation trials demonstrated that all the means displayed similar type-I error rates when the variances were homogenous regardless of the distribution shape, sample size and the number of groups. When homogeneity of variances assumption was not satisfied, the most reliable result was obtained by using trimmed mean in terms of keeping the type-I error rate at nominal alpha level and it was followed by modified and winsorized means. The most biased results were obtained when arithmetic mean was used.Öğe Multiple Linear Regression versus Automatic Linear Modelling(Arquivo Brasileiro Medicina Veterinaria Zootecnia, 2024) Genc, S.; Mendes, M.In this study, performances of Multiple Linear Regression and Automatic Linear Modelling are compared for different sample sizes and number of predictors. A comprehensive Monte Carlo simulation study was carried out for this purpose. Random numbers generated from multivariate normal distribution by using RNMVN function of IMSL library of Microsoft FORTRAN Developer Studio composed the material of this study. Results of the simulation study showed that the sample size and the number of predictors are the main factors that lead to produce different results. Although both methods gave very similar results especially when studied with large sample sizes (n >= 100), the Automatic linear modelling is preferred for analyzing data sets due to its simplicity in analyzing data and interpreting the results, ability to present results visually and providing more detailed information especially studying large complex data sets. It will be beneficial to use the Automatic linear modelling especially in analyzing massive and complex data sets for the purposes of investigating the relationships between one continuous dependent and 10 or more predictors and determine the factors that affect the response or target variable. At the same time, it will also be possible to evaluate the effect of each predictor with a more detailed response.
