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Showing 1 to 15 of 21 results Save | Export
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Pellerine, Liam P.; Petterson, Jennifer L.; Shivgulam, Madeline E.; Johansson, Peter J.; Hettiarachchi, Pasan; Kimmerly, Derek S.; Frayne, Ryan J.; O'Brien, Myles W. – Measurement in Physical Education and Exercise Science, 2023
Device-based measures often rely on the positive relationship between walking cadence and metabolic equivalents of task (METs) to estimate physical activity. It is unknown whether this relationship remains during jogging/running. The study purpose was to investigate the relationships between METs, cadence, and step length during walking and…
Descriptors: Physical Activity Level, Predictor Variables, Physical Activities, Young Adults
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Pérez-Castilla, Alejandro; Fernandes, John F. T.; Rojas, F. Javier; García-Ramos, Amador – Measurement in Physical Education and Exercise Science, 2021
This study explored the influence of different take-off thresholds on the reliability and magnitude of countermovement jump (CMJ) performance variables. Twenty-three men were tested on two separate sessions. CMJ performance variables were obtained against three external loads (0.5-30-60 kg) using three take-off thresholds: 10 N (arbitrary value of…
Descriptors: Physical Activities, Performance Tests, Reliability, College Students
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Soowoong Hwang; Jungjoon Kim; Ilhyeok Park – Measurement in Physical Education and Exercise Science, 2025
This study investigates the predictive validity of lower extremity strength, strength asymmetry, and soccer-specific fitness in talent identification among elite male youth soccer players. Employing a Retrospective Cohort design, we established a cohort consisting of K-League registered youth players, totaling 219 individuals (all males, aged 16…
Descriptors: Team Sports, Physical Fitness, Talent Identification, Males
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Battista, Rebecca A.; Bouldin, Erin D.; Pfeiffer, Karin A.; Pacewicz, Christine E.; Siegel, Shannon R.; Martin, Eric M.; True, Larissa; Branta, Crystal F.; Haubenstricker, John; Seefeldt, Vern – Measurement in Physical Education and Exercise Science, 2021
Participation in youth sport is positively associated with physical fitness and performance. The purpose of the current study was to examine if physical fitness measures during childhood and early adolescence predicted high school sport participation. Participants included youth in the Michigan State University Motor Performance Study. Measures…
Descriptors: Physical Fitness, Predictor Variables, High School Students, Student Athletes
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Casey J. Metoyer; Katherine Sullivan; Lee J. Winchester; Mark T. Richardson; Michael R. Esco; Michael V. Fedewa – Measurement in Physical Education and Exercise Science, 2025
Relative adiposity (%Fat) was measured using a smartphone-based application in a convenience sample of adults aged 20-52 years (n = 32, 68.7% female, 84.3% White/Caucasian, 26.7 ± 3.5 kg/m2) across different body positions (Anterior versus Posterior) on consecutive days (Day 1 versus Day 2). A reference photo was obtained from the posterior view…
Descriptors: Adults, Body Composition, Handheld Devices, Computer Assisted Instruction
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Min Pan; Wei-Ting Hsu – Measurement in Physical Education and Exercise Science, 2025
Constraints-led approach (CLA) is widely used in physical education (PE). This four-phased study aimed to develop a self-report measurement of students' perceived constraints support in PE. The relationships among students' perceived constraints support, competence and novelty need satisfaction, motivation, effort, and engagement in PE were also…
Descriptors: Physical Education, Student Attitudes, Test Construction, Test Validity
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Martin, Eric M.; True, Larissa; Pfeiffer, Karin A.; Siegel, Shannon R.; Branta, Crystal F.; Wisner, Dave; Haubenstricker, John; Seefeldt, Vern – Measurement in Physical Education and Exercise Science, 2021
Research tracking sport participation from youth to adulthood is relatively rare, as is research that tracks youth sport participation with regard to adult physical activity (PA) levels, especially in the United States. Aims of this study were: 1) To investigate the degree to which sport participation tracked across youth, adolescence, and early…
Descriptors: Athletics, Participation, Children, Adolescents
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Mahar, Matthew T.; Welk, Gregory J.; Rowe, David A. – Measurement in Physical Education and Exercise Science, 2018
Purpose: To develop models to estimate aerobic fitness (VO[subscript 2]max) from PACER performance in 10- to 18-year-old youth, with and without body mass index (BMI) as a predictor. Method: Youth (N = 280) completed the PACER and a maximal treadmill test to assess VO[subscript 2]max. Validation and cross-validation groups were randomly formed to…
Descriptors: Exercise, Physical Fitness, Preadolescents, Adolescents
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Yeatts, Paul E.; Barton, Mitch; Henson, Robin K.; Martin, Scott B. – Measurement in Physical Education and Exercise Science, 2017
A common practice in general linear model (GLM) analyses is to interpret regression coefficients (e.g., standardized ß weights) as indicators of variable importance. However, focusing solely on standardized beta weights may provide limited or erroneous information. For example, ß weights become increasingly unreliable when predictor variables are…
Descriptors: Predictor Variables, Correlation, Multiple Regression Analysis, Physical Fitness
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Kern, Ben D.; Graber, Kim C. – Measurement in Physical Education and Exercise Science, 2017
Program satisfaction, self-efficacy to change, and willingness to change, are dispositions that influence physical education teacher change. The study purpose was to validate an instrument measuring program satisfaction, self-efficacy to change, and willingness to change relative to teachers' likelihood to change. A 15-item Teacher Change…
Descriptors: Physical Education Teachers, Test Validity, Questionnaires, Self Efficacy
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Webb, Carrie; Vehrs, Pat R.; George, James D.; Hager, Ronald – Measurement in Physical Education and Exercise Science, 2014
The purpose of this study was to develop a step test with a personalized step rate and step height to predict cardiorespiratory fitness in 80 college-aged males and females using the self-reported perceived functional ability scale and data collected during the step test. Multiple linear regression analysis yielded a model (R = 0.90, SEE = 3.43…
Descriptors: Tests, Physical Fitness, College Students, Multiple Regression Analysis
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Myers, Nicholas D.; Brincks, Ahnalee M.; Beauchamp, Mark R. – Measurement in Physical Education and Exercise Science, 2010
The primary purpose of this tutorial is to succinctly review some options for, and consequences of, centering Level 1 predictors in commonly applied cross-sectional two-level models. It is geared toward both practitioners and researchers. A general understanding of multilevel modeling is necessary prior to understanding the subtleties of centering…
Descriptors: Models, Statistical Analysis, Predictor Variables, Athletes
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Brammer, Chris L.; Stager, Joel M.; Tanner, Dave A. – Measurement in Physical Education and Exercise Science, 2012
The purpose of the authors in this study was to predict the mean swim time of the top eight swimmers in swim events at the 2012 Olympic Games based upon prior Olympic performances from 1972 through 2008. Using the mean top eight time across all years, a best fit power curve [time = a x year[superscript b]] was calculated and used to predict the…
Descriptors: Distance Education, Applied Linguistics, Vocational Interests, Supervisory Training
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Cremades, J. Gualberto; Wated, Guillermo; Wiggins, Matthew S. – Measurement in Physical Education and Exercise Science, 2011
The purpose of the present study was to investigate whether combining the two dimensions of anxiety (i.e., intensity and direction) by using a multiplicative model would strengthen the prediction of burnout. Collegiate athletes (N = 157) completed the Athlete Burnout Questionnaire as well as a trait version of the Competitive State Anxiety…
Descriptors: College Students, Burnout, Measures (Individuals), Anxiety
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Gaudreau, Patrick; Fecteau, Marie-Claude; Perreault, Stephane – Measurement in Physical Education and Exercise Science, 2010
The goal of this article is to present a series of conceptual, statistical, and practical issues in the modeling of multi-level dyadic data. Distinctions are made between distinguishable and undistinguishable dyads and several types of independent variables modeled at the dyadic level of analysis. Multi-level modeling equations are explained in a…
Descriptors: Data, Models, Predictor Variables, Equations (Mathematics)
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