A Comparison of Efficiency for Homogeneity of Variance Tests under Log-normal Distribution

In this paper, we compare five homogeneity of variance tests which are Bartlett’s test, Levene’s test, Cochran’s test, O’Brien’s test and Jackknife test. Considering their ability to control probability of type I error and the power of the test, when groups of population are distributed in log-normal distribution. The equal sample sizes are defined as 10, 15, 30 and 50 at the significance is 0.05. The results show that the Levene’s test become the best test for the high skewed distribution. For the lowed skew distribution, the Cochran’s test is the best test when a variance of group is different to the others. Moreover, Bartlett’s test provides the highest power when variances of all populations are different.

The Balakrishnan-Alpha-Beta-Skew-Normal Distribution: Properties and Applications

In this paper, a new form of alpha-beta-skew distribution is proposed under Balakrishnan (2002) mechanism and investigated some of its related distributions. The most important feature of this new distribution is that it is versatile enough to support both unimodal and bimodal as well as multimodal behaviors of the distribution. The moments, distributional properties and some extensions of the proposed distribution have also been studied. Finally, the suitability of the proposed distribution has been tested by conducting data fitting experiment and comparing the values of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) with the values of some other related distributions. Likelihood Ratio testis used for discriminating between normal and the proposed distributions.

Identifying talent: public organisation with skewed performance scores

PurposeThis study aims to draw lessons on how talent identification becomes a critical factor in the field of talent management (TM).Design/methodology/approachA simulation approach with three developed scenarios is used in the paper. The first utilised the standard deviation of skewed performance scores, the second applied the standard deviation of normalised data and the third practised a percentile approach. Concerning the normalisation process of employee performance data, the paper proposed a weighted function to address skewness.FindingsThe results indicate that the process of identifying talent using a nine-grid box is sensitive to changes in the classification criteria used, indicating a bias in identifying talent. In sum, using a standard deviation approach using transformation data is the most appropriate choice for use in performance data with a skewed distribution.Practical implicationsThe Government of West Java Province, Indonesia, can use the simulation results to objectively identify excellent civil servants and develop an appropriate TM strategy. A similar process treatment can be implemented in other organisations that have skew distribution issues.Originality/valueThis paper introduces a weighted function approach to address practical problems in the unsymmetrical distribution of employee performance scores when identifying talent using a TM framework. It shows the application of a unique mathematical technique to solve issues found in the field of human resources management systems.

Study on Change Rules of Factors Affecting Gas Loss during Coalbed Air Reverse Circulation Sampling

The gas loss in sampling is the root of coalbed gas content measurement error. The pressure and particle size have a significant impact on the gas loss. Using the self-developed coal particle pneumatic pipeline transportation experimental system, this study investigated the pressure and particle size changes in the sampling pipeline. It is found that the sampling process can be divided into four stages: no flow field stage, sample outburst stage, stable conveying stage, and tail purging stage. The extreme pressure in the sampling pipeline appears at the sample outburst stage; and the pressure in the pipeline has levelled off after sharp decrease in the stable conveying stage. It is also found that the extreme pressure increases first and then decreases with the increase of particle size. The duration of outburst stage is negatively correlated with particle size, and that of stable conveying stage is positively correlated with particle size. In addition, the results show that the loss rate of 1–3 mm particles is the smallest after the test but that particles less than 1 mm increase by about two times and particles greater than 3 mm decrease by more than three times. The study also shows that the particle size distribution of coal samples is a single peak with left skew distribution, and the gas reverse circulation sampling test does not change the location of the peak but makes it higher and sharper. The single size coal sample is more likely to collide than the mixture. This study can help to advance the understanding of impact factors on gas loss during reverse circulation sampling.

Psychometric Performance of Prosocial Tendencies Measure for Undergraduates in Guangdong Province

Objective: To analyze the psychometric performance of Prosocial Tendencies Measure (PTM) for undergraduates in Guangdong province. Methods: Stratified random sampling method was used to select 1109 undergraduates from 10 colleges in Guangdong province.PTM was used to investigate them. Cronbach's α coefficient and split-half reliability were used to analyze the internal consistency of the questionnaire.Convergent validity, discriminant validity and factor analysis were used to evaluate its structural validity. Celling and floor effect were used to analyze its sensitivity. Results: Cronbach's α coefficient of the total questionniar was 0.94 and cronbach's α coefficient of 6 dimensions were 0.82~0.87, which met with the requirements of the group comparison. Spearman - Brown split-half coefficient of the total questionniar was 0.95, and the split half reliability of 6 dimensions were 0.83~0.88. The calibration success rate of convergent validity and discriminant validity of the 6 dimensions were all 100%. One component obtained from 23 items which cumulative variance contribution rate was 82.31%. The total score and scores of 6 dimensions were all positive skew distribution, with floor effect in 6 dimensions. Conclusions: The psychometric properties of PTM for undergraduates in Guangdong was valid and reliable.

Changes of Occupational Noise-Induced Hearing Loss due to Working in the Steel Industry and Associated Effective Factors: Application of Bayesian Multivariate Multilevel Modeling using Skew Distribution : Rate of NIHL in Steel Workers

Background:There have been a limited number of studies on the relationships between time and occupational and demographical variables with the mean changes of low-frequency hearing (LFH) and high-frequency hearing (HFH). Objectives: This study investigated the rate of occupational noise-induced hearing loss (NIHL) due to working in the steel industry and associated effective factors. Materials and Methods: This historical cohort study was conducted within 2000 to 2010. Two LFH and HFH definitions of NIHL were used in this study. The average changes of LFH and HFL were considered the response variables. In addition, time and occupational (i.e., shift work and work experience) and demographical (i.e., age and educational level) variables were regarded as the independent variables. For data analysis, Bayesian multivariate multilevel modeling using skew distribution and OpenBUGS (version 3.2.2) and R (version 2.13.2) software were used in this study. Results: The present study was performed on 1,959 male workers with a mean age of 36.64±3.92 years. Among these subjects, 913 (46.6%), 134 (6.8%), and 912 (46.6%) participants were day workers, weekly-rotating shift workers, and routinely-rotating shift workers, respectively. The obtained results showed that age, work experience, educational level, and shift work had significant relationships with the changes of LFH and HFH. Conclusion:Overall, the findings of this 10-year historical cohort study demonstrated a relationship between time and demographical and occupational variables with the changes of LFH and HFL. Therefore, it is recommended to design preventive measures to reduce the deleterious effects of such variables on LFH and HFL.

Anxiety levels among Iranian health care workers during the COVID-19 surge: A cross-sectional study

The recent surge in COVID-19 cases has exposed health care workers (HCWs) to a wide range of psychological stressors and predisposed them to anxiety-related disorders. Here, we investigated the anxiety level in this population. This multi-center, cross-sectional study was performed on 1038 HCWs in 14 hospitals during the COVID-19 pandemic. Beck anxiety inventory (BAI) was used to measure the level of anxiety in this population. In all, 1038 hospital staffs with a mean age of 36.30±8.23 years old participated in this study. Most participants were 31 to 40 years old (43.2), female (87.6%), and nurses (49.5%). The BAI scores for the participants were in a positive skew distribution, with a score range of 0-63, a median of 12 and a mean value of 15.30±11.43. Of the 1038 hospital staff, 411 (39.6%) had moderate to severe anxiety. The anxiety level was significantly higher in health care workers ≤40 years old, women, and nurses. Gender, age, and working positions had the most relation with anxiety, respectively. It seems that HCWs experienced a high level of anxiety in the COVID-19 outbreak. One of the important measures in each epidemic is doing supportive care to maintain the mental well-being of HCWs, especially in higher risk groups, including younger HCWs, women, and nurses.

Modeling Responses and Response Times in Tests With the Hierarchical Model and the Three-Parameter Lognormal Distribution

The hierarchical model of van der Linden is the most popular model for responses and response times in tests. It is composed of two separate submodels—one for the responses and one for the response times—that are joined at a higher level. The submodel for the response times is based on the lognormal distribution. The lognormal distribution is a skew distribution with a support from zero to infinity. Such a support is unrealistic as the solution process demands a minimal processing time that sets a response time threshold. Ignoring this response time threshold misspecifies the model and threatens the validity of model-based inferences. In this article, the response time model of van der Linden is replaced by a model that is based on the three-parameter lognormal distribution. The three-parameter lognormal distribution extends the lognormal distribution by an additional location parameter that bounds the support away from zero. Two different approaches to model fitting are proposed and evaluated with regard to parameter recovery in a simulation study. The extended model is applied to two data sets. In both data sets, the extension improves the fit of the hierarchical model.

The Log-Balakrishnan-Alpha-Skew-Normal Distribution and its Applications

In this paper, a new form of log-alpha-skew distribution is proposed by the same methodology of Venegas et al. (2016) and investigated some of its related distributions. The moments and distributional properties of the proposed distribution are also discussed. Also, the appropriateness of this distribution are checked by performing the data fitting experiment and comparing the values of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) with the values of some other known distributions. Likelihood ratio test is used for discriminating between normal and the proposed distributions.

Bayesian Skew Normal Seemingly Unrelated Regression Modelling of Gross Regional Domestic Product

The assumption of the error normality in the regression model was often questioned especially in cases where there was an outlier, which causes the behavior of asymmetric data. To overcome this, without data transformation, we could use skew distribution. This distribution was very important and applicable in various fields of science such as finance, economics, actuarial science, medicine, biology, investment. Skew Normal distributions had been proven to have a convenient for calculating bias in data with asymmetric behavior. This study aims to model SUR with Skew Normal error using Bayesian approach applied to East Java GRDP data. This study would compared two types of models, namely models with Normal distributed errors and models with Skew Normal distributed errors. The result of parameter estimation with Bayesian approach shows that SUR Skew Normal model was more suitable for East Java GRDP modeling rather than using normal error model. This was based on their smaller Root of Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) value.Â