scholarly journals Psychometric properties of the Burnout Inventory for Referees (BIR) for Brazilian Basketball Referees

2021 ◽  
Vol 21 (3) ◽  
pp. 243-257
Author(s):  
Flávia Renata De Almeida ◽  
Daniel Alvarez Pires ◽  
Robert Weinberg ◽  
Maria Regina Ferreira Brandão

El objetivo principal de este trabajo fue verificar las propiedades psicométricas del Inventario de Burnout para Árbitros en árbitros de baloncesto brasileños. Fueron evaluados un total de 395 árbitros de baloncesto (edad: 35.11 ± 9.18 años), de ambos sexos (masculino = 319 y femenino = 76), con un tiempo de experiencia promedio de 12.34 ± 7.83 años, quienes respondieron cuestionarios de identificación demográfica, Burnout Inventory for Brazilian Basketball Referees (BIR-AB) y Brunel Mood Scale for Basketball Referees (BRUMS-AB). La validez factorial se estimó mediante el análisis factorial confirmatorio (AFC) con el método de estimación de máxima verosimilitud. Como se rechazó la homocedasticidad, la comparación entre grupos se realizó mediante ANOVA con corrección de Welch seguido del post-test de Games-Howell. La correlación entre las puntuaciones de los factores BIR-AB y las variables edad y duración de la experiencia se evaluó mediante el análisis de correlación de Pearson (r). El nivel de significancia adoptado fue del 5%. Tras la realización del AFC e inserción del modelo jerárquico de segundo orden (MHSO), se propuso un nuevo modelo, denominado BIR-AB (Burnout Inventory for Referees para árbitros brasileños de baloncesto), que contiene dos dimensiones negativas (agotamiento físico y emocional y despersonalización) y una positiva (rendimiento deportivo), con índices de ajuste adecuados, se constató una confiabilidad aceptable e invariante entre el género y en la muestra de prueba / validación y la validez divergente. The main goal of this paper was to verify the psychometric properties of the Burnout Inventory for Referees on Brazilian basketball referees (BIR-AB). A total of 395 basketball referees were evaluated (age: 35.11 ± 9.18 years), of both gender (male = 319 and female = 76), with an average experience time of 12.34 ± 7.83 years, who answered demographic identification questionnaires, Burnout Inventory for Brazilian Basketball Referees (BIR-AB) and Brunel Mood Scale for Basketball Referees (BRUMS-AB). Factor validity was estimated using Confirmatory Factor Analysis (CFA) with the Maximum Likelihood estimation method. As homoscedasticity was rejected, the comparison between groups was performed using ANOVA with Welch's correction followed by the Games-Howell post-test. The correlation between the scores of the BIR-AB factors and the variables age and length of experience was assessed using Pearson's Correlation Analysis (r). The level of significance adopted was 5%. After the performance of the CFA and insertion of the second-order hierarchical model (MHSO), a new model was proposed, called BIR-AB, containing two negative dimensions (physical and emotional exhaustion and depersonalization) and a positive (sport performance), with adequate adjustment indexes, acceptable and invariant reliability between the gender and in the test/validation sample and the divergent validity was attested. O objetivo principal desse estudo foi verificar as propriedades psicométricas do Burnout Inventory for Referees para árbitros brasileiros de basquetebol. Foram avaliados 395 árbitros de basquetebol (idade: 35,11 ± 9,18 anos), de ambos os sexos (masculino=319 e feminino=76), com tempo médio de experiência de 12,34 ± 7,83 anos, que responderam aos questionários de identificação demográfica, Burnout Inventory for Brazilian Basketball Referees (BIR-AB) e Brunel Mood Scale for Basketball Referees (BRUMS-AB). A validade fatorial foi estimada utilizando-se a Análise Fatorial Confirmatória (AFC) com método de estimação da Máxima Verossimilhança. Como a homocedasticidade foi rejeitada, a comparação entre os grupos foi realizada por meio da ANOVA com correção de Welch seguido pelo pós-teste de Games-Howell. A correlação entre os escores dos fatores do BIR-AB e as variáveis idade e tempo de atuação foi avaliada a partir da Análise de Correlação de Pearson (r). O nível de significância adotado foi 5%. Após a realização da AFC e inserção do modelo hierárquico de segunda ordem (MHSO), um novo modelo foi proposto, chamado de BIR-AB (Burnout Inventory for Referees para árbitros brasileiros de basquetebol), contendo duas dimensões negativas (exaustão física e emocional e ) e uma positiva (desempenho esportivo), com índices adequados de ajustamento, confiabilidade aceitável e invariante entre os sexos e na amostra teste/validação e a validade divergente foi atestada.

2018 ◽  
Vol 3 (01) ◽  
pp. 59
Author(s):  
Sumardjono Jono ◽  
Heni Ardila

The purpose of this study is to determine and prove whether the variables of  the marketing mix significantly has influenced  the consumer’s decision making to buy the product at PT. Griya Pagelaran Bogor. The population of this study are the number of unknown sampling determination using Maximum Likelihood estimation method by taking samples of consumers who their needs has met with the researcher requirement as many as 150 respondents. The analytical method has used is Structural Equation Modeling (SEM) using AMOS 21 program. The result of the research shows that 1) Product Variables have a significance level of 0.05 which is 1,965 > 1,96 and value (p) probability 0,49 ≤ 0.05. Then Ha is accepted and significant effect. 2) Variable Price level of significance 0.05 is 2.023 > 1.96 and has a probability of 0.43 which is below 0.05. And the value (p) probability ≤ 0.05 then Ha is accepted and significant effect. 3) Place Variables significance level of 0.05 is 2.251 > 1.96 and has a probability of 0.24 which  is below 0.05. And the value (p) probability ≤ 0.05 then Ha is accepted and significant effect. 4) Promotion Variables 0.05 level of significance is 3.435 > 1.96 and has a probability in accordance with the recommended. And the value (p) probability ≤ 0.05 then Ha accepted and significant effect.Keywords: Marketing Mix, Consumer Purchase Decision, SEM


METRON ◽  
2021 ◽  
Author(s):  
Carlo Cavicchia ◽  
Pasquale Sarnacchiaro

AbstractTeachers’ performances also depend on whether and how they are satisfied with their job. Therefore, Teacher Job Satisfaction must be considered as the driver of teachers’ accomplishments. To plan future policies and improve the overall teaching process, it is crucial to understand which factors mostly contribute to Teacher Job Satisfaction. A Common Assessment Framework and Education questionnaire was administered to 163 Italian public secondary school teachers to collect data, and a second-order factor analysis was used to detect which factors impact on Teacher Job Satisfaction, and to what extent. This model-based approach guarantees to detect factors which respect important properties: unidimensionality and reliability. All the coefficients are estimated according to the maximum likelihood estimation method in order to make inference on the parameters and on the validity of the model. Moreover, a new multi-group test for higher-order factor analysis was proposed and implemented. Finally, we analyzed in detail whether the factors impacting Teacher Job Satisfaction are characterized by gender.


Author(s):  
Shuguang Song ◽  
Hanlin Liu ◽  
Mimi Zhang ◽  
Min Xie

In this paper, we propose and study a new bivariate Weibull model, called Bi-levelWeibullModel, which arises when one failure occurs after the other. Under some specific regularity conditions, the reliability function of the second event can be above the reliability function of the first event, and is always above the reliability function of the transformed first event, which is a univariate Weibull random variable. This model is motivated by a common physical feature that arises fromseveral real applications. The two marginal distributions are a Weibull distribution and a generalized three-parameter Weibull mixture distribution. Some useful properties of the model are derived, and we also present the maximum likelihood estimation method. A real example is provided to illustrate the application of the model.


2006 ◽  
Vol 3 (4) ◽  
pp. 1603-1627 ◽  
Author(s):  
W. Wang ◽  
P. H. A. J. M. van Gelder ◽  
J. K. Vrijling ◽  
X. Chen

Abstract. The Lo's R/S tests (Lo, 1991), GPH test (Geweke and Porter-Hudak, 1983) and the maximum likelihood estimation method implemented in S-Plus (S-MLE) are evaluated through intensive Mote Carlo simulations for detecting the existence of long-memory. It is shown that, it is difficult to find an appropriate lag q for Lo's test for different AR and ARFIMA processes, which makes the use of Lo's test very tricky. In general, the GPH test outperforms the Lo's test, but for cases where there is strong autocorrelations (e.g., AR(1) processes with φ=0.97 or even 0.99), the GPH test is totally useless, even for time series of large data size. Although S-MLE method does not provide a statistic test for the existence of long-memory, the estimates of d given by S-MLE seems to give a good indication of whether or not the long-memory is present. Data size has a significant impact on the power of all the three methods. Generally, the power of Lo's test and GPH test increases with the increase of data size, and the estimates of d with GPH test and S-MLE converge with the increase of data size. According to the results with the Lo's R/S test (Lo, 1991), GPH test (Geweke and Porter-Hudak, 1983) and the S-MLE method, all daily flow series exhibit long-memory. The intensity of long-memory in daily streamflow processes has only a very weak positive relationship with the scale of watershed.


2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Mohammed Haiek ◽  
Youness El Ansari ◽  
Nabil Ben Said Amrani ◽  
Driss Sarsri

In this paper, we propose a stochastic model to describe over time the evolution of stress in a bolted mechanical structure depending on different thicknesses of a joint elastic piece. First, the studied structure and the experiment numerical simulation are presented. Next, we validate statistically our proposed stochastic model, and we use the maximum likelihood estimation method based on Euler–Maruyama scheme to estimate the parameters of this model. Thereafter, we use the estimated model to compare the stresses, the peak times, and extinction times for different thicknesses of the elastic piece. Some numerical simulations are carried out to illustrate different results.


2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Yifan Sun ◽  
Xiang Xu

As a widely used inertial device, a MEMS triaxial accelerometer has zero-bias error, nonorthogonal error, and scale-factor error due to technical defects. Raw readings without calibration might seriously affect the accuracy of inertial navigation system. Therefore, it is necessary to conduct calibration processing before using a MEMS triaxial accelerometer. This paper presents a MEMS triaxial accelerometer calibration method based on the maximum likelihood estimation method. The error of the MEMS triaxial accelerometer comes into question, and the optimal estimation function is established. The calibration parameters are obtained by the Newton iteration method, which is more efficient and accurate. Compared with the least square method, which estimates the parameters of the suboptimal estimation function established under the condition of assuming that the mean of the random noise is zero, the parameters calibrated by the maximum likelihood estimation method are more accurate and stable. Moreover, the proposed method has low computation, which is more functional. Simulation and experimental results using the consumer low-cost MEMS triaxial accelerometer are presented to support the abovementioned superiorities of the maximum likelihood estimation method. The proposed method has the potential to be applied to other triaxial inertial sensors.


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