Sports are a meaningful context in which many young people participate,and youth sports teams may be a viable way to promote optimal development.Sports comprises all forms of physical activities that contribute to phy...Sports are a meaningful context in which many young people participate,and youth sports teams may be a viable way to promote optimal development.Sports comprises all forms of physical activities that contribute to physical fitness,mental well-being and social interaction.Participation in sport improves the development of peer relationships,establishes the notion of trust and builds teamwork skills.The purpose of this study was to see the impact of sports participation on intelligence among boys.The present study was conducted on 300 male subjects between age group 14 and 17 years.Subjects were divided into following three groups(Group 1-Team Sports Group,Group 2-Individual Sports Group,Group 3-Non-participant Group)using a questionnaire for Sports Activity participation survey.Each group has 100 students.To assess intelligence of the selected subjects,verbal intelligence test prepared by Dr.P.Srinivasan was adopted.Appropriate tool was used to assess the parameters.The results show that majority i.e.64.7%of the subjects were found to be average intelligent and 22.7 superiorly intelligent.It was revealed that sports participation has no association withrelation to intelligence(IQ)and revealed that there was no significant effect found on intelligence level of the subjects who participated in sports as well as the non-participants.展开更多
The prevalence of a disease in a population is defined as the proportion of people who are infected. Selection bias in disease prevalence estimates occurs if non-participation in testing is correlated with disease sta...The prevalence of a disease in a population is defined as the proportion of people who are infected. Selection bias in disease prevalence estimates occurs if non-participation in testing is correlated with disease status. Missing data are commonly encountered in most medical research. Unfortunately, they are often neglected or not properly handled during analytic procedures, and this may substantially bias the results of the study, reduce the study power, and lead to invalid conclusions. The goal of this study is to illustrate how to estimate prevalence in the presence of missing data. We consider a case where the variable of interest (response variable) is binary and some of the observations are missing and assume that all the covariates are fully observed. In most cases, the statistic of interest, when faced with binary data is the prevalence. We develop a two stage approach to improve the prevalence estimates;in the first stage, we use the logistic regression model to predict the missing binary observations and then in the second stage we recalculate the prevalence using the observed data and the imputed missing data. Such a model would be of great interest in research studies involving HIV/AIDS in which people usually refuse to donate blood for testing yet they are willing to provide other covariates. The prevalence estimation method is illustrated using simulated data and applied to HIV/AIDS data from the Kenya AIDS Indicator Survey, 2007.展开更多
文摘Sports are a meaningful context in which many young people participate,and youth sports teams may be a viable way to promote optimal development.Sports comprises all forms of physical activities that contribute to physical fitness,mental well-being and social interaction.Participation in sport improves the development of peer relationships,establishes the notion of trust and builds teamwork skills.The purpose of this study was to see the impact of sports participation on intelligence among boys.The present study was conducted on 300 male subjects between age group 14 and 17 years.Subjects were divided into following three groups(Group 1-Team Sports Group,Group 2-Individual Sports Group,Group 3-Non-participant Group)using a questionnaire for Sports Activity participation survey.Each group has 100 students.To assess intelligence of the selected subjects,verbal intelligence test prepared by Dr.P.Srinivasan was adopted.Appropriate tool was used to assess the parameters.The results show that majority i.e.64.7%of the subjects were found to be average intelligent and 22.7 superiorly intelligent.It was revealed that sports participation has no association withrelation to intelligence(IQ)and revealed that there was no significant effect found on intelligence level of the subjects who participated in sports as well as the non-participants.
文摘The prevalence of a disease in a population is defined as the proportion of people who are infected. Selection bias in disease prevalence estimates occurs if non-participation in testing is correlated with disease status. Missing data are commonly encountered in most medical research. Unfortunately, they are often neglected or not properly handled during analytic procedures, and this may substantially bias the results of the study, reduce the study power, and lead to invalid conclusions. The goal of this study is to illustrate how to estimate prevalence in the presence of missing data. We consider a case where the variable of interest (response variable) is binary and some of the observations are missing and assume that all the covariates are fully observed. In most cases, the statistic of interest, when faced with binary data is the prevalence. We develop a two stage approach to improve the prevalence estimates;in the first stage, we use the logistic regression model to predict the missing binary observations and then in the second stage we recalculate the prevalence using the observed data and the imputed missing data. Such a model would be of great interest in research studies involving HIV/AIDS in which people usually refuse to donate blood for testing yet they are willing to provide other covariates. The prevalence estimation method is illustrated using simulated data and applied to HIV/AIDS data from the Kenya AIDS Indicator Survey, 2007.
