Pub Date : 2019-10-15DOI: 10.1285/I20705948V12N2P320
F. Lecciso, Annalisa Levante, F. Signore, S. Petrocchi
Abstract The Quantitative-CHecklist for Autism in Toddler (Q-CHAT) is a screening measure developed to detect the early signs of risk of Autism Spectrum Disorders (ASD) in children from 18-24 months of life. After a critical analysis of the validation studies that have analyzed the Q-CHAT, the present paper aimed at testing the structural validity of the questionnaire through Confirmatory Factor Analysis and determining whether it is invariant across gender. Furthermore, the study examined the internal validity of the measure, calculated the risk cut-off score, and evaluated gender differences. Five hundred forty-five questionnaires were completed by parents of children from unselected population (age M = 19.9 months; sd = 1 month; age range = 18-21; 254 girls). Findings gave tolerable demonstration of the expected three-factor structure and measurement invariance across gender. Gender differences were also found as well as correlations among factors as a demonstration of internal validity. The risk cut-off of 43 was calculated based on the 95 th percentile of the distribution. In conclusion, the present study demonstrated preliminary findings of the validity of the Q-CHAT for Italian children. However, our findings suggested also that three items need to be reformulated because they show several psychometric problems and, after that, the factorial validity, measurement invariance, and internal validity should be re-tested. Further longitudinal studies are also needed to examine the validity criterion of the Q-CHAT to test the cut-off score.
{"title":"Preliminary evidence of the structural validity and measurement invariance of the Quantitative-CHecklist for Autism in Toddler (Q-CHAT) on Italian unselected children","authors":"F. Lecciso, Annalisa Levante, F. Signore, S. Petrocchi","doi":"10.1285/I20705948V12N2P320","DOIUrl":"https://doi.org/10.1285/I20705948V12N2P320","url":null,"abstract":"Abstract The Quantitative-CHecklist for Autism in Toddler (Q-CHAT) is a screening measure developed to detect the early signs of risk of Autism Spectrum Disorders (ASD) in children from 18-24 months of life. After a critical analysis of the validation studies that have analyzed the Q-CHAT, the present paper aimed at testing the structural validity of the questionnaire through Confirmatory Factor Analysis and determining whether it is invariant across gender. Furthermore, the study examined the internal validity of the measure, calculated the risk cut-off score, and evaluated gender differences. Five hundred forty-five questionnaires were completed by parents of children from unselected population (age M = 19.9 months; sd = 1 month; age range = 18-21; 254 girls). Findings gave tolerable demonstration of the expected three-factor structure and measurement invariance across gender. Gender differences were also found as well as correlations among factors as a demonstration of internal validity. The risk cut-off of 43 was calculated based on the 95 th percentile of the distribution. In conclusion, the present study demonstrated preliminary findings of the validity of the Q-CHAT for Italian children. However, our findings suggested also that three items need to be reformulated because they show several psychometric problems and, after that, the factorial validity, measurement invariance, and internal validity should be re-tested. Further longitudinal studies are also needed to examine the validity criterion of the Q-CHAT to test the cut-off score.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"12 1","pages":"320-340"},"PeriodicalIF":0.7,"publicationDate":"2019-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1285/I20705948V12N2P320","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44420845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-14DOI: 10.1285/I20705948V12N2P341
H. Panahi
In this article, the point and interval estimation of parameters for an in-verse Burr distribution based on progressively rst-failure censored sampleis studied. In point estimation, the maximum likelihood and Bayesian meth-ods are developed for estimating the unknown parameters. An expectation-maximization algorithm is applied for computing the maximum likelihoodestimators. The Bayes estimates relative to both the symmetric and asym-metric loss functions are provided using the Lindley's approximation andthe Metropolis-Hastings algorithm. In interval estimation, approximate andexact condence intervals with the exact condence region for the two parameters have been introduced. Moreover, the proposed methods are carriedout to a real data set contains the spreading of nanodroplet impingementonto a solid surface in order to demonstrate the applicabilities.
{"title":"Different Estimation Methods and Joint Condence Region for the Inverse Burr Distribution Based on Progressively First-Failure Censored Sample with Application to the Nanodroplet Data","authors":"H. Panahi","doi":"10.1285/I20705948V12N2P341","DOIUrl":"https://doi.org/10.1285/I20705948V12N2P341","url":null,"abstract":"In this article, the point and interval estimation of parameters for an in-verse Burr distribution based on progressively rst-failure censored sampleis studied. In point estimation, the maximum likelihood and Bayesian meth-ods are developed for estimating the unknown parameters. An expectation-maximization algorithm is applied for computing the maximum likelihoodestimators. The Bayes estimates relative to both the symmetric and asym-metric loss functions are provided using the Lindley's approximation andthe Metropolis-Hastings algorithm. In interval estimation, approximate andexact condence intervals with the exact condence region for the two parameters have been introduced. Moreover, the proposed methods are carriedout to a real data set contains the spreading of nanodroplet impingementonto a solid surface in order to demonstrate the applicabilities.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"12 1","pages":"341-361"},"PeriodicalIF":0.7,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1285/I20705948V12N2P341","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43027813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-14DOI: 10.1285/I20705948V12N2P508
Z. Algamal
Beta regression model has received much attention in several science fields in modeling proportions or rates data. Selecting a small subset of relevant variables from a large number of variables is an important task for building a predictive regression model. This paper proposes employing the particle swarm optimization algorithm as a variable selection method in the beta regression model with varying dispersion. The performance of the proposed method is evaluated through simulation and real data application. Results demonstrate the superiority of the proposed method compared to other competitor methods including corrected Akaike information criterion, corrected Schwarz information criterion, and corrected Hannan and Quinn criterion. Thus, the proposed method can efficiently helpful as a variable selection tool in the beta regression model with varying dispersion.
{"title":"A particle swarm optimization method for variable selection in beta regression model","authors":"Z. Algamal","doi":"10.1285/I20705948V12N2P508","DOIUrl":"https://doi.org/10.1285/I20705948V12N2P508","url":null,"abstract":"Beta regression model has received much attention in several science fields in modeling proportions or rates data. Selecting a small subset of relevant variables from a large number of variables is an important task for building a predictive regression model. This paper proposes employing the particle swarm optimization algorithm as a variable selection method in the beta regression model with varying dispersion. The performance of the proposed method is evaluated through simulation and real data application. Results demonstrate the superiority of the proposed method compared to other competitor methods including corrected Akaike information criterion, corrected Schwarz information criterion, and corrected Hannan and Quinn criterion. Thus, the proposed method can efficiently helpful as a variable selection tool in the beta regression model with varying dispersion.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"12 1","pages":"508-519"},"PeriodicalIF":0.7,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1285/I20705948V12N2P508","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44059279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-14DOI: 10.1285/I20705948V12N2P477
Ann-Ni Soh, Chin-Hong Puah, M. Arip
The composite leading indicators approach has been popularised in general business and property forecasting extensively, but only rarely in a tourism framework. By utilising the National Bureau of Economic Research (NBER) approach in the construction of a tourism cycle indicator (TCI) for Maldives, a significant signalling attribute regarding international tourists arrivals (TA) to Maldives can be determined. This study spanned approximately two decades of data (2000-2017). Both logarithm forms of TCI and TA with seasonal adjustment are detrended by Hodrick-Prescott (HP) filter. Turning points are detected using Bry-Boschan (BB) dating algorithm. This study explored the possibility of a TCI to capture the information needed for policy planning, risk monitoring and community development. Empirical findings highlighted that the forecasting ability of TCI is vital in reducing crisis burden and should be considered by Maldivians policymakers and tourism industry players.
{"title":"Construction of tourism cycle indicator: A signalling tool for tourism market dynamics","authors":"Ann-Ni Soh, Chin-Hong Puah, M. Arip","doi":"10.1285/I20705948V12N2P477","DOIUrl":"https://doi.org/10.1285/I20705948V12N2P477","url":null,"abstract":"The composite leading indicators approach has been popularised in general business and property forecasting extensively, but only rarely in a tourism framework. By utilising the National Bureau of Economic Research (NBER) approach in the construction of a tourism cycle indicator (TCI) for Maldives, a significant signalling attribute regarding international tourists arrivals (TA) to Maldives can be determined. This study spanned approximately two decades of data (2000-2017). Both logarithm forms of TCI and TA with seasonal adjustment are detrended by Hodrick-Prescott (HP) filter. Turning points are detected using Bry-Boschan (BB) dating algorithm. This study explored the possibility of a TCI to capture the information needed for policy planning, risk monitoring and community development. Empirical findings highlighted that the forecasting ability of TCI is vital in reducing crisis burden and should be considered by Maldivians policymakers and tourism industry players.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"12 1","pages":"477-490"},"PeriodicalIF":0.7,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1285/I20705948V12N2P477","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44248911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-14DOI: 10.1285/I20705948V12N2P465
Mohammad Al-Talib
For the important role of confidence intervals in statistical inference, we present in this article the shortest pivotal confidence interval using an entropy measure called the Resistor-Average distance, two examples are used to show the application of the proposed technique which include a simulation study.
{"title":"On the Shortest Pivotal Confidence Intervals: An Entropy Measure Technique","authors":"Mohammad Al-Talib","doi":"10.1285/I20705948V12N2P465","DOIUrl":"https://doi.org/10.1285/I20705948V12N2P465","url":null,"abstract":"For the important role of confidence intervals in statistical inference, we present in this article the shortest pivotal confidence interval using an entropy measure called the Resistor-Average distance, two examples are used to show the application of the proposed technique which include a simulation study.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"12 1","pages":"465-476"},"PeriodicalIF":0.7,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43410616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-14DOI: 10.1285/I20705948V12N2P405
A. Mulenga, M. Faias, P. Mota, J. Pina
The normality of the log-return of stock prices is often assumed by the market players in order to use some useful results, as for instance, the Black-Scholes formula for pricing European options. However, several studies regarding different indexes have shown that the normality assumption of the returns usually fails. In this paper we analyse the normality assumption for intra-day and inter-day log-returns, comparing opening prices and/or closing prices for a large number of companies quoted in the Nasdaq Composite index. We use the Pearson's Chi-Square, Kolmogorov-Smirnov, Anderson-Darling, Shapiro-Wilks and Jarque-Bera goodness-of-fit tests to study the normality assumption.We find that the failure rate in the normality assumption for the log-return of stock prices is not the same for intra-day and inter-day prices, is somewhat test dependent and strongly dependent on some extreme price observations. To the best of our knowledge, this is the first study on the normality assumption for the log-return of stock prices dealing simultaneously with a large number of companies and normality tests, and at the same time considering various scenarios of intra-day, inter-day prices and data trimming.
股票价格对数回报的正态性通常由市场参与者假设，以便使用一些有用的结果，例如，欧洲期权定价的Black-Scholes公式。然而，关于不同指数的几项研究表明，收益率的正态性假设通常是失败的。在本文中，我们分析了日内和日间日志回报的正态性假设，比较了纳斯达克综合指数中大量公司的开盘价和/或收盘价。我们使用Pearson’s Chi Square、Kolmogorov Smirnov、Anderson Darling、Shapiro Wilks和Jarque Bera拟合优度检验来研究正态性假设。我们发现，对于日内和日间价格，股票价格对数回报的正态性假设中的失败率并不相同，在一定程度上取决于测试，并且强烈依赖于一些极端价格观察。据我们所知，这是首次对股票价格对数回归的正态性假设进行研究，同时处理大量公司和正态性测试，同时考虑日内、日间价格和数据修剪的各种场景。
{"title":"What happens when the stock markets are closed","authors":"A. Mulenga, M. Faias, P. Mota, J. Pina","doi":"10.1285/I20705948V12N2P405","DOIUrl":"https://doi.org/10.1285/I20705948V12N2P405","url":null,"abstract":"The normality of the log-return of stock prices is often assumed by the market players in order to use some useful results, as for instance, the Black-Scholes formula for pricing European options. However, several studies regarding different indexes have shown that the normality assumption of the returns usually fails. In this paper we analyse the normality assumption for intra-day and inter-day log-returns, comparing opening prices and/or closing prices for a large number of companies quoted in the Nasdaq Composite index. We use the Pearson's Chi-Square, Kolmogorov-Smirnov, Anderson-Darling, Shapiro-Wilks and Jarque-Bera goodness-of-fit tests to study the normality assumption.We find that the failure rate in the normality assumption for the log-return of stock prices is not the same for intra-day and inter-day prices, is somewhat test dependent and strongly dependent on some extreme price observations. To the best of our knowledge, this is the first study on the normality assumption for the log-return of stock prices dealing simultaneously with a large number of companies and normality tests, and at the same time considering various scenarios of intra-day, inter-day prices and data trimming.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"12 1","pages":"405-415"},"PeriodicalIF":0.7,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1285/I20705948V12N2P405","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43455887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-14DOI: 10.1285/I20705948V12N2P453
Rehad Shamany, Nada Nazar Alobaidi, Z. Algamal
The presence of multicollinearity among the explanatory variables has undesirable effects on the maximum likelihood estimator (MLE). The inverse Gaussian regression (IGR) model is a well-known model in application when the response variable positively skewed. To address the problem of multicollinearity, a two-parameter estimator is proposed (TPE). The TPE enjoys the advantage that its mean squared error (MSE) is less than MLE. The TPE is derived and the performance of this estimator is investigated under several conditions. Monte Carlo simulation results indicate that the proposed estimator performs better than the MLE estimator in terms of MSE. Furthermore, a real chemometrics dataset application is utilized and the results demonstrate the excellent performance of the suggested estimator when the multicollinearity is present in IGR model.
{"title":"A new two-parameter estimator for the inverse Gaussian regression model with application in chemometrics","authors":"Rehad Shamany, Nada Nazar Alobaidi, Z. Algamal","doi":"10.1285/I20705948V12N2P453","DOIUrl":"https://doi.org/10.1285/I20705948V12N2P453","url":null,"abstract":"The presence of multicollinearity among the explanatory variables has undesirable effects on the maximum likelihood estimator (MLE). The inverse Gaussian regression (IGR) model is a well-known model in application when the response variable positively skewed. To address the problem of multicollinearity, a two-parameter estimator is proposed (TPE). The TPE enjoys the advantage that its mean squared error (MSE) is less than MLE. The TPE is derived and the performance of this estimator is investigated under several conditions. Monte Carlo simulation results indicate that the proposed estimator performs better than the MLE estimator in terms of MSE. Furthermore, a real chemometrics dataset application is utilized and the results demonstrate the excellent performance of the suggested estimator when the multicollinearity is present in IGR model.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"12 1","pages":"453-464"},"PeriodicalIF":0.7,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1285/I20705948V12N2P453","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47077555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-14DOI: 10.1285/I20705948V12N2P429
A. Al-Omari, Khaldoon M. Alhyasat, K. Ibrahim, M. Bakar
In this paper, a new distribution called weighted size biased two-parameterAkash distribution (WSBTPAD) is proposed. The WSBTPAD is a newmodication of the size biased two-parameter Akash distribution. The mainstatistical properties of the WSBTPAD are derived and proved. These prop-erties include the moments, particularly the rth moment, moment generatingfunction, harmonic mean, Bonferroni and Lorenz curves as well as the Giniindex. Also, the mean deviations of the population mean and median andthe Renyi entropy are presented. The reliability analysis of the random vari-able following WSBTPAD random variable are discussed. The method ofmaximum likelihood estimation is considered for estimating the parametersof the distribution. The distribution of order statistics from the WSBTPADare provided.
{"title":"Power Length-Biased Suja Distribution: Properties and Application","authors":"A. Al-Omari, Khaldoon M. Alhyasat, K. Ibrahim, M. Bakar","doi":"10.1285/I20705948V12N2P429","DOIUrl":"https://doi.org/10.1285/I20705948V12N2P429","url":null,"abstract":"In this paper, a new distribution called weighted size biased two-parameterAkash distribution (WSBTPAD) is proposed. The WSBTPAD is a newmodication of the size biased two-parameter Akash distribution. The mainstatistical properties of the WSBTPAD are derived and proved. These prop-erties include the moments, particularly the rth moment, moment generatingfunction, harmonic mean, Bonferroni and Lorenz curves as well as the Giniindex. Also, the mean deviations of the population mean and median andthe Renyi entropy are presented. The reliability analysis of the random vari-able following WSBTPAD random variable are discussed. The method ofmaximum likelihood estimation is considered for estimating the parametersof the distribution. The distribution of order statistics from the WSBTPADare provided.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"12 1","pages":"429-452"},"PeriodicalIF":0.7,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1285/I20705948V12N2P429","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48932058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-14DOI: 10.1285/I20705948V12N2P416
G. Bruno, Carolina Corea
Index of production in construction and building permits are two indica- tors used to describe the short-term evolution of the construction sector. In particular, the former measures the level of activity in terms of the sector output, whereas the latter are meant to anticipate production in construction in the very near future, as they represent the administrative applications to start building activity. Nevertheless, for a number of reasons to be detected, building permits do not always act as a leading indicator of the construction sector short-term performance. To investigate whether there are any leading- lagging relations between these two variables, a descriptive analysis based on cross-correlations has been preliminarily carried out and then supplemented by the application of a VAR (Vector Autoregressive) model, used to analyse Granger causality within a cointegrated system of the two variables.
{"title":"Do building permits act as a leading indicator of Italy short-term production in construction?","authors":"G. Bruno, Carolina Corea","doi":"10.1285/I20705948V12N2P416","DOIUrl":"https://doi.org/10.1285/I20705948V12N2P416","url":null,"abstract":"Index of production in construction and building permits are two indica- tors used to describe the short-term evolution of the construction sector. In particular, the former measures the level of activity in terms of the sector output, whereas the latter are meant to anticipate production in construction in the very near future, as they represent the administrative applications to start building activity. Nevertheless, for a number of reasons to be detected, building permits do not always act as a leading indicator of the construction sector short-term performance. To investigate whether there are any leading- lagging relations between these two variables, a descriptive analysis based on cross-correlations has been preliminarily carried out and then supplemented by the application of a VAR (Vector Autoregressive) model, used to analyse Granger causality within a cointegrated system of the two variables.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"12 1","pages":"416-428"},"PeriodicalIF":0.7,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46236980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-14DOI: 10.1285/I20705948V12N2P362
R. Salmerón, S. Gómez-Haro
Obtaining relevant information about the performance of sports teams and players involves an ongoing analysis of factors that affect individual performance, including the use of tools that help estimate the athletic performance of professional players and improve decision making by managers and coaches. The aim of this work is to establish which statistics for basketball players discriminate between high and low performance and regularity using a performance-regularity index. The sample comprised players from the Spanish professional basketball league, the ACB League during the 2014-2015. We divided the sample into players with low, medium and high performance and regularity, and a discriminant analysis associated high numbers of rebounds, assists and steals with high performance and regularity and higher numbers of 3-point shots, turnovers and fouls with low performance and regularity. These results should help coaches and sports managers to design templates and sports gambling strategies that improve performance in their teams.
{"title":"High performance of professional basketball play- ers and the settings to measure their regularity: evidence from the Spanish ACB League","authors":"R. Salmerón, S. Gómez-Haro","doi":"10.1285/I20705948V12N2P362","DOIUrl":"https://doi.org/10.1285/I20705948V12N2P362","url":null,"abstract":"Obtaining relevant information about the performance of sports teams and players involves an ongoing analysis of factors that affect individual performance, including the use of tools that help estimate the athletic performance of professional players and improve decision making by managers and coaches. The aim of this work is to establish which statistics for basketball players discriminate between high and low performance and regularity using a performance-regularity index. The sample comprised players from the Spanish professional basketball league, the ACB League during the 2014-2015. We divided the sample into players with low, medium and high performance and regularity, and a discriminant analysis associated high numbers of rebounds, assists and steals with high performance and regularity and higher numbers of 3-point shots, turnovers and fouls with low performance and regularity. These results should help coaches and sports managers to design templates and sports gambling strategies that improve performance in their teams.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"12 1","pages":"362-379"},"PeriodicalIF":0.7,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1285/I20705948V12N2P362","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41859404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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