Claire Mills, Mark De Ste Croix, David James, Stephen-Mark Cooper
{"title":"开发新型校准模型,预测职业足球运动员的全身密度。","authors":"Claire Mills, Mark De Ste Croix, David James, Stephen-Mark Cooper","doi":"10.1080/24733938.2023.2166680","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Questions continue to be raised about the validity that is in existence to estimate D<sub>b</sub>, in professional male footballer players.</p><p><strong>Methods: </strong>Phase 1: <i>n</i> = 28 anthropometric variables were used on <i>n</i> = 206 footballers, using regression analyses to determine standard error of estimate and <i>R</i><sup>2</sup>. A cut-off correlation coefficient set at <i>r</i> = 0.950 and 90% <i>R</i><sup>2</sup>. Phase 2: all variables (<i>z</i>-scores, <math><mover><mi>x</mi><mo>-</mo></mover></math> = 0.0, SD = ±1.0) to help reduce heteroscedasticity, β, <i>r</i>, <i>t</i>, significance of <i>t</i> and <i>P-</i>values were calculated. Phase 3: a forced stepwise-backwards regression analysis approach with nine predictors which met the acceptance criteria (<i>r</i> = 0.950, <i>R</i><sup>2</sup> = 90% and β weights) was used to develop a '<i>best fit</i>' and a '<i>practical</i>' calibration model. Phase 4: cross-validation of the two newly developed calibration method using LoA.</p><p><strong>Results: </strong>The 'best fit' model SEM (0.115 g ml<sup>-1</sup>), the highest <i>R</i><sup>2</sup> (6.6%) (<i>P</i> ≤ 0.005), whereas the 'practical' calibration model SEM (0.115 g ml<sup>-1</sup>), <i>R</i><sup>2</sup> (4.7%) (<i>P</i> ≤ 0.005) with <i>r</i> values = 0.271 and 0.596 and <i>R</i><sup>2</sup> (%) coefficients = 0.3526 for the 'best fit' and 'practical' calibration models, respectively (<i>P</i> = 0.01).</p><p><strong>Conclusions: </strong>The two calibration models supported an ecologically and statistically valid contribution and can provide sound judgements about professional footballers' body composition.</p>","PeriodicalId":74767,"journal":{"name":"Science & medicine in football","volume":" ","pages":"170-178"},"PeriodicalIF":0.0000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of novel calibration model(s) to predict whole-body density in professional football players.\",\"authors\":\"Claire Mills, Mark De Ste Croix, David James, Stephen-Mark Cooper\",\"doi\":\"10.1080/24733938.2023.2166680\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Questions continue to be raised about the validity that is in existence to estimate D<sub>b</sub>, in professional male footballer players.</p><p><strong>Methods: </strong>Phase 1: <i>n</i> = 28 anthropometric variables were used on <i>n</i> = 206 footballers, using regression analyses to determine standard error of estimate and <i>R</i><sup>2</sup>. A cut-off correlation coefficient set at <i>r</i> = 0.950 and 90% <i>R</i><sup>2</sup>. Phase 2: all variables (<i>z</i>-scores, <math><mover><mi>x</mi><mo>-</mo></mover></math> = 0.0, SD = ±1.0) to help reduce heteroscedasticity, β, <i>r</i>, <i>t</i>, significance of <i>t</i> and <i>P-</i>values were calculated. Phase 3: a forced stepwise-backwards regression analysis approach with nine predictors which met the acceptance criteria (<i>r</i> = 0.950, <i>R</i><sup>2</sup> = 90% and β weights) was used to develop a '<i>best fit</i>' and a '<i>practical</i>' calibration model. Phase 4: cross-validation of the two newly developed calibration method using LoA.</p><p><strong>Results: </strong>The 'best fit' model SEM (0.115 g ml<sup>-1</sup>), the highest <i>R</i><sup>2</sup> (6.6%) (<i>P</i> ≤ 0.005), whereas the 'practical' calibration model SEM (0.115 g ml<sup>-1</sup>), <i>R</i><sup>2</sup> (4.7%) (<i>P</i> ≤ 0.005) with <i>r</i> values = 0.271 and 0.596 and <i>R</i><sup>2</sup> (%) coefficients = 0.3526 for the 'best fit' and 'practical' calibration models, respectively (<i>P</i> = 0.01).</p><p><strong>Conclusions: </strong>The two calibration models supported an ecologically and statistically valid contribution and can provide sound judgements about professional footballers' body composition.</p>\",\"PeriodicalId\":74767,\"journal\":{\"name\":\"Science & medicine in football\",\"volume\":\" \",\"pages\":\"170-178\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science & medicine in football\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/24733938.2023.2166680\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/1/17 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science & medicine in football","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/24733938.2023.2166680","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/17 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
引言方法:第一阶段:对 n = 206 名足球运动员使用 28 个人体测量变量,使用回归分析确定估计标准误差和 R2:第一阶段:对 n = 206 名足球运动员使用了 n = 28 个人体测量变量,使用回归分析确定估计标准误差和 R2。相关系数的临界值设定为 r = 0.950 和 90% R2。第 2 阶段:计算所有变量(z-分数,x- = 0.0,SD = ±1.0)以帮助减少异方差、β、r、t、t 的显著性和 P 值。第 3 阶段:使用符合验收标准(r = 0.950、R2 = 90% 和 β 权重)的 9 个预测因子进行强制逐步回归分析,以建立 "最合适 "和 "实用 "校准模型。第 4 阶段:使用 LoA 对两种新开发的校准方法进行交叉验证:结果:"最佳拟合 "模型 SEM(0.115 g ml-1)的 R2(6.6%)最高(P ≤ 0.005),而 "实用 "校准模型 SEM(0.115 g ml-1)的 R2(4.7%)最高(P ≤ 0.005),"最佳拟合 "和 "实用 "校准模型的 r 值分别为 0.271 和 0.596,R2(%)系数分别为 0.3526(P = 0.01):这两个校准模型在生态学和统计学上都是有效的,可以对职业足球运动员的身体成分做出正确的判断。
Development of novel calibration model(s) to predict whole-body density in professional football players.
Introduction: Questions continue to be raised about the validity that is in existence to estimate Db, in professional male footballer players.
Methods: Phase 1: n = 28 anthropometric variables were used on n = 206 footballers, using regression analyses to determine standard error of estimate and R2. A cut-off correlation coefficient set at r = 0.950 and 90% R2. Phase 2: all variables (z-scores, = 0.0, SD = ±1.0) to help reduce heteroscedasticity, β, r, t, significance of t and P-values were calculated. Phase 3: a forced stepwise-backwards regression analysis approach with nine predictors which met the acceptance criteria (r = 0.950, R2 = 90% and β weights) was used to develop a 'best fit' and a 'practical' calibration model. Phase 4: cross-validation of the two newly developed calibration method using LoA.
Results: The 'best fit' model SEM (0.115 g ml-1), the highest R2 (6.6%) (P ≤ 0.005), whereas the 'practical' calibration model SEM (0.115 g ml-1), R2 (4.7%) (P ≤ 0.005) with r values = 0.271 and 0.596 and R2 (%) coefficients = 0.3526 for the 'best fit' and 'practical' calibration models, respectively (P = 0.01).
Conclusions: The two calibration models supported an ecologically and statistically valid contribution and can provide sound judgements about professional footballers' body composition.