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…

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…

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…

The purpose of this study was to develop a multiple linear regression model to predict treadmill VO[subscript 2max] scores using both exercise and non-exercise data. One hundred five college-aged participants (53 male, 52 female) successfully completed a submaximal cycle ergometer test and a maximal graded exercise test on a motorized treadmill.…

This study was designed to develop a single-stage submaximal treadmill jogging (TMJ) test to predict VO[subscript 2]max in fit adults. Participants (N = 400; men = 250 and women = 150), ages 18 to 40 years, successfully completed a maximal graded exercise test (GXT) at 1 of 3 laboratories to determine VO[subscript 2]max. The TMJ test was completed…