运动员退役年龄预测模型的建立

chae jin seok
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The stepwise regression analysis method was applied to develop reliable and valid retirement predictive regression function. The degree of relevance was shown by multiple correlation coefficient between predicted age calculated by the predictive function and actual retirement age. Significance level was .05 for all tests. The 8 predictive function are presented according to the procedure above. (retirement age of female athlete)= 24.097+1.778*(physical limitation 11)-1.142*(job plan29), (retirement age of male athlete)= 23.498+1.334*(popularity 2)-1.126*(exercise attitude 20)+1.021*(competitiveness 7)-1.020* (job plan 29)+0.871*(economy 18)-1.905*(administration 22)-1.024*(administration 23)+.778*(interpersonal relationship 13), (retirement age of combat sports)=23.158+.688*(physical limitation 11)-1.790*(job plan 29)+0.960*(popularity 1)-0.656*(exercise attitude 16)+0.747*(job plan 33)+0.643*(economy 18)-0.461*(administration 23)+.606*(injury 46), (retirement age of non-combat sports)=20.741+ 1.637*(popularity 2)-1.270*(exercise attitude 20)+0.942*(competitiveness 7)+2.061*(family 5)-3.291*(administration 21)+1.082*(administration 25)+1.192(interpersonal relationship 8), (retirement age of individual sports)=27.414-1.295*(job plan 29)+1.463*(physical limitation 15)+0.972*(popularity 1)-0.639* (exercise 16), (retirement age of group sports)= 21.950+1.950*(popularity 2)-1.318*(exercise attitude 20)+4.635*(interpersonal relationship 6)-3.337*(addiction 41), (retirement age of undergraduate athlete)= 21.950+1.950*(popularity 2)-1.318*(exercise attitude 20)+4.635*(interpersonal relationship 6) -3.337*(addiction 41), (retirement age of unemployed and professional athlete)= 27.808-0.874* (exercise attitude 19)+1.287*(competitiveness 8)-1.402*(administration 21)+0.757*(popularity 2).","PeriodicalId":93448,"journal":{"name":"International journal of applied sports sciences : IJASS","volume":"31 1","pages":"101-114"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of retirement age prediction model for athletes\",\"authors\":\"chae jin seok\",\"doi\":\"10.24985/ijass.2019.31.2.101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The purpose of this study is to present retirement age predictive functions of athletes that can be utilized as data to reduce psychological shock of athletes from retirement and prepare for the future. 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引用次数: 0

摘要

本研究的目的是提出运动员退役年龄的预测函数,作为数据来减少运动员退役后的心理冲击,为未来做好准备。为此,在大韩体育奥林匹克委员会运动员登记制度上登记了3年以上的大学生、失业者、专业人士等退役运动员作为对象进行了调查。为方便抽样,采用分层抽样。通过咨询专家,对退休因素问卷的内容效度进行了检验。通过开放式问卷收集了72名退休人员的意见,在第一部分样本数据的基础上咨询专家后,使用了260人的样本进行第一部分和第二部分。采用逐步回归分析方法,建立了可靠有效的退休预测回归函数。预测函数计算的预测年龄与实际退休年龄之间的多重相关系数表示相关性的程度。所有检验的显著性水平为0.05。根据上述步骤,给出了8个预测函数。 (女运动员退休年龄)= 24.097+1.778*(身体限制11)-1.142*(工作计划29), (男运动员退休年龄)= 23.498+1.334*(人气2)-1.126*(运动态度20)+1.021*(竞争力7)-1.020*(工作计划29)+0.871*(经济18)-1.905*(管理22)-1.024*(管理23)+。778*(人际关系13), (搏击运动退休年龄)=23.158+。688*(身体限制11)-1.790*(工作计划29)+0.960*(人气1)-0.656*(锻炼态度16)+0.747*(工作计划33)+0.643*(经济18)-0.461*(行政23)+。606*(伤害46),(非战斗运动退休年龄)=20.741+ 1.637*(人气2)-1.270*(运动态度20)+0.942*(竞争力7)+2.061*(家庭5)-3.291*(管理21)+1.082*(管理25)+1.192(人际关系8), (个人运动退休年龄)=27.414-1.295*(工作计划29)+1.463*(身体限制15)+0.972*(人气1)-0.639*(运动16),(团体运动退休年龄)= 21.950+1.950*(人气2)-1.318*(运动态度20)+4.635*(人际关系6)-3.337*(成瘾41),(大学生运动员退休年龄)= 21.950+1.950*(人气2)-1.318*(运动态度20)+4.635*(人际关系6)-3.337*(成瘾41),(失业和职业运动员退休年龄)= 27.808-0.874*(运动态度19)+1.287*(竞争力8)-1.402*(行政21)+0.757*(人气2)。
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Development of retirement age prediction model for athletes
The purpose of this study is to present retirement age predictive functions of athletes that can be utilized as data to reduce psychological shock of athletes from retirement and prepare for the future. To accomplish such purpose, athletes who retired as an undergraduate, unemployed or professional registered on the athlete registration system of the Korean Sport & Olympic Committee for three years were selected as the population. Stratified sampling was used for convenience sampling. Content validity of a retirement factor questionnaire was examined by consulting with experts. Opinions of 72 retirees were collected through an open questionnaire, and samples of 260 persons were used in the first and second parts after consulting with experts based on first sample data. The stepwise regression analysis method was applied to develop reliable and valid retirement predictive regression function. The degree of relevance was shown by multiple correlation coefficient between predicted age calculated by the predictive function and actual retirement age. Significance level was .05 for all tests. The 8 predictive function are presented according to the procedure above. (retirement age of female athlete)= 24.097+1.778*(physical limitation 11)-1.142*(job plan29), (retirement age of male athlete)= 23.498+1.334*(popularity 2)-1.126*(exercise attitude 20)+1.021*(competitiveness 7)-1.020* (job plan 29)+0.871*(economy 18)-1.905*(administration 22)-1.024*(administration 23)+.778*(interpersonal relationship 13), (retirement age of combat sports)=23.158+.688*(physical limitation 11)-1.790*(job plan 29)+0.960*(popularity 1)-0.656*(exercise attitude 16)+0.747*(job plan 33)+0.643*(economy 18)-0.461*(administration 23)+.606*(injury 46), (retirement age of non-combat sports)=20.741+ 1.637*(popularity 2)-1.270*(exercise attitude 20)+0.942*(competitiveness 7)+2.061*(family 5)-3.291*(administration 21)+1.082*(administration 25)+1.192(interpersonal relationship 8), (retirement age of individual sports)=27.414-1.295*(job plan 29)+1.463*(physical limitation 15)+0.972*(popularity 1)-0.639* (exercise 16), (retirement age of group sports)= 21.950+1.950*(popularity 2)-1.318*(exercise attitude 20)+4.635*(interpersonal relationship 6)-3.337*(addiction 41), (retirement age of undergraduate athlete)= 21.950+1.950*(popularity 2)-1.318*(exercise attitude 20)+4.635*(interpersonal relationship 6) -3.337*(addiction 41), (retirement age of unemployed and professional athlete)= 27.808-0.874* (exercise attitude 19)+1.287*(competitiveness 8)-1.402*(administration 21)+0.757*(popularity 2).
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