Dr. Yuanlong Liu [yuanlong.liu@wmich.edu] Website

After a long period of search, the search committee of the journal Measurement in Physical Education and Exercise Science (MPEES) has decided to offer Dr. Yuanlong Liu the editorship. Dr. Liu's responsibility as the editor will start from June 1st, 2006. Dr. Liu is an associate professor in the Department of Health, Physical Education and Recreation at Western Michigan University. MPEES is a peer-reviewed research journal. In 1997, Measurement in Physical Education and Exercise Science Volume 1(1) of the new, peer-reviewed quarterly reached subscribers. Now with Volume 9(3) and 35 issues already in the archive, there is ample validation of both the original need and the presence of a growing audience of readers over the world. From the outset, the sponsoring agency has been the American Association for Active Lifestyles and Fitness, the American Association for Leisure and Recreation (AAALF/AALR) and the Measurement and Evaluation Council. The umbrella organization is the American Alliance of Physical Education, Recreation and Dance (AAHPERD). AAHPERD is the largest organization of professionals supporting and assisting those involved in physical education, leisure, fitness, dance, health promotion, and education and all specialties related to achieving a healthy lifestyle. Dr. Liu joined the Western Michigan University in 1998. Author and coauthor for research manuscripts and a few book chapters, he has conducted refereed and invited presentations, completed many journal reviews for several academic journals, and participated in a number of grant projects. His professional service has included secretary and advisory board member of the Measurement and Evaluation Council, editorial advisory board member of the International Sports Journal, and reviewer board member of the Measurement in Physical Education and Exercise Science. He is a Fellow Member of the American Alliance of Health, Physical Education, Recreation and Dance and a professional member of the American College of Sport Medicine. He is also a faculty senator at the Western Michigan University. He received the MPEES' Reviewer of the Year award in 2003.

RESEARCH INTEREST

My main research interests are the measurement and evaluation issues in education and physical performances, effectiveness of competition structures in sports, statistical issues in repeated measurements, computer simulation and application in measurement and evaluation, and instrument validation in education, health and exercise related fields.

Consulting and Supervision

The statistical consulting and data analysis has been offered to students and faculty members. Master thesis supervision was involved. I have been doing program evaluation for grant funded research projects.

1.Liu, Y., & Schutz, R. (2003). Statistical validity of using a simple ratio in human kinetics research. Research Quarterly for Exercise Science and Sport, 74, 226-235.

The purposes of this study were to investigate the validity of the simple ratio (Y=X1/X2) and three alternative deflation models (Y=(X1-a)/X2, Y=X1/X2k, and Y=(X1-a)/X2k ), and to examine how the relative variation of the numerator and denominator variables affects the reliability of a ratio variable. The results support the conclusion that the validity of a deflation model depends on the statistical characteristics of the particular component variables used, and an optimal deflation model for all variables may not exist. Therefore, it is recommended that different models be fitted to each empirical data set to determine the best deflation model. With respect to reliability, it was shown that the reliability of a simple ratio is affected by the coefficients of variation, and the within- and between-trial correlations between the numerator and denominator variables. It was recommended that researchers should compute the reliability of the derived ratio scores, and not assume that strong reliabilities in the numerator and denominator measures automatically lead to high reliability in the ratio measures.

Key Words: ratio variable, deflation model, reliability, validity.

2. Liu, Y., & Wang, Y. (2004). Reliability of the kinetic measures under different heel conditions during normal working. Measurement in Physical Education and Exercise Science, 8, 21-31.

The purpose of this study was to determine and compare the reliability of three dimension reaction forces and impulses in walking with three different heel shoe conditions. The results suggest that changing the height of the heels affects mainly the reliability of the ground reaction force and impulse measures on the medial and lateral dimension and not the vertical and the anterior-posterior dimensions. The force and impulse measures are more reliable in the high heel shoe condition than in the low heel shoe condition. To keep the consistent (reliable) walking pattern, more muscular stress has to be placed on the foot muscles when one wears high heel shoes. These results lead us to believe that further research is needed to elucidate the difference of the muscle activities where one wears high heel shoes. The influence of muscle fatigue on pathological symptoms in walking also needs additional research.

Key Words: Reliability, Force, Impulse.

3. Liu, Y., & Schutz, R. (2003). Determining an optimal game structure: Overtime in the national hockey league. International Sports Journal, 7, 1-8.

This study was to answer the following questions: Does a five-minute overtime in national hockey league reduce the number of tied games? Is a short five-minute overtime a "fair" contest in that the better team has the greater probability of winning? To what extent would a 10-, 15-, or 20-minute overtime substantially improve the fairness of the contest and reduce the number of tied games? Statistics on the number of regular season overtime games that took place since the five minute overtime format was introduced in 1983, and the outcome and time of the overtime goals for all Stanley Cup play-offs games 1972 to 2001 served as the data for this investigation. The results indicate that both the old (1983-1999) and the current (1999-2001) five-minute sudden-death overtime formats used in the NHL regular season games are useful in reducing the number of tied games, although only one-third of all overtime games are resolved with the five-minute overtime period. Additionally, the stronger team, as reflected by relative league standings, is more likely (p .65) to score first in an overtime, thus lending support for the validity of overtime to discriminate among team playing abilities. Finally, lengthening the overtime period to 10 minutes is recommended as it is expected that this would result in approximately 60% to 65% of overtime games ending in a decision.

KEY WORDS: ice hockey, tie games

4. Liu, Y. (2004). Track and Field Performance Data and Prediction Models: Promises and Fallacies. In Sergiy Butenko, Panos Pardalos, and Jaime Gil-Lafuente (Eds). Economics, Management, and Optimization in Sports. New York: Springer-Verlag.

#.1 Introduction
Prediction is always a fascinating obsession no matter what we predict. We predict what tomorrow's weather will be, which team will win the game, who will be the next president of the United States, how fast one will run and how high one will jump, and even how much money we will make next year. Mathematical and statistical models have been used to predict future events in different disciplines. Some prediction models can be used to predict specific magnitudes of an event in the future. For example, because of the high technology development in the last two decades, the models used for weather forecasting became more and more accurate. In some other fields, the prediction models are actually not for a specific magnitude of an event in the future but for predicting various developmental trends in the future. For example, statistical models are commonly used for predicting the developmental trends in stocks but not for predicting specific values of the stocks.
In track and field, the curiosity with respect to the limits of human athletic performances has always been of interest to athletes, coaches and scientists (Liu, 2002). Since track and field performances are the oldest competitive sports, the interest in a human being's ability and accomplishment in running, jumping and throwing has a long and diversified history. Mathematicians, statisticians, physiologists and operational researchers have developed numerous models to predict future performances, world records and 'ultimate' performances in track and field, and to compare male and female performances (Liu and Schutz 1998).
There have been many publications regarding the prediction of track and field performances. Some of them are opinion based and lack scientific support. Others used track and field data and mathematical and statistical models. There has been some confusion as to what the track and field performance data provide and what the prediction models show. A review of the prediction models in literature leads us to believe that there is no prediction model available to accurately predict the future magnitude of any performance in track and field (Liu, 2002, Liu and Schutz, 1998). So, what are the promises and fallacies of the prediction models in track and field? The primary focus of this chapter is a discussion of the following issues in predicting track and field performances: Track and field performances data and its validity in predicting future performances and the promises and fallacies of the prediction models.

[Edited by Zan Gao]