Search Results

You are looking at 1 - 10 of 14 items for :

  • "quantile regression" x
  • Refine by Access: All Content x
Clear All
Restricted access

Susan Paudel, Alice J. Owen, Stephane Heritier, and Ben J. Smith

correlates, as the completed questionnaires were cross-checked at the field level and any missing information was collected during subsequent visits. The descriptive analysis was carried out using Stata SE 14 (StataCorp, College Station, TX). Quantile regression (QR) was used to examine the potential

Restricted access

Erik Lundkvist, Henrik Gustafsson, Paul Davis, and Peter Hassmén

The aims of this study were to (a) examine the associations between workaholism and work-related exhaustion and (b) examine associations between work–home/ home–work interference and work-related exhaustion in 261 Swedish coaches. Quantile regression showed that workaholism is only associated with exhaustion for coaches who score high on exhaustion, that negative work–home interference has a stronger association with exhaustion than negative home–work interference, and that the coaches on a mean level scored low on all measured constructs. In addition, coaches in the higher percentiles have a higher risk for burnout. Our results highlight the importance of studying coach exhaustion with respect to aspects that extend beyond the sports life.

Restricted access

S. Morgan Hughey, Marilyn E. Wende, Ellen W. Stowe, Andrew T. Kaczynski, Jasper Schipperijn, and J. Aaron Hipp

research objectives, a model building process was used with 4 separate quantile regression analyses. The outcome variable for all analyses was minutes of MVPA reported by individuals. The MVPA variable was not normally distributed; therefore, quantile regression was used, as it is a nonparametric method

Open access

Gregory J. Welk, Pedro F. Saint-Maurice, Philip M. Dixon, Paul R. Hibbing, Yang Bai, Gabriella M. McLoughlin, and Michael Pereira da Silva

provide an appropriate evaluation of the developed models. All analyses were conducted using SAS (version 9.4; Cary, NC), and we used p  < .05 to define statistical significance. In the calibration phase, we used quantile regression ( Koenker, 2019 ) to predict the accelerometer median percentage of time

Restricted access

Vanesa España-Romero, Jonathan A. Mitchell, Marsha Dowda, Jennifer R. O’Neill, and Russell R. Pate

The purpose of this study was to examine the associations between sedentary behavior and moderate to vigorous physical activity (MVPA), measured by accelerometry, with body mass index (BMI) and waist circumference in 357 preschool children. Linear mixed models were used adjusting for race/ethnicity, parental education, and preschool. Follow-up analyses were performed using quantile regression. Among boys, MVPA was positively associated with BMI z-score (b = 0.080, p = .04) but not with waist circumference; quantile regression showed that MVPA was positively associated with BMI z-score at the 50th percentile (b = 0.097, p < .05). Among girls, no associations were observed between sedentary behavior and MVPA in relation to mean BMI z-score and mean waist circumference. Quantile regression indicated that, among girls at the 90th waist circumference percentile, a positive association was found with sedentary behavior (b = 0.441, p < .05), and a negative association was observed with MVPA (b = −0.599, p < .05); no associations were found with BMI z-score. In conclusion, MVPA was positively associated with BMI z-score among boys, and MVPA was negatively associated and sedentary behavior was positively associated with waist circumference among girls at the 90th percentile.

Restricted access

Lanay M. Mudd, Jim Pivarnik, Claudia B. Holzman, Nigel Paneth, Karin Pfeiffer, and Hwan Chung


Leisure-time physical activity (LTPA) is recommended during pregnancy and has been associated with lower risk of delivering a large infant. We sought to characterize the effect of LTPA across the entire birth weight distribution.


Women enrolled in the Pregnancy Outcomes and Community Health (POUCH) Study (1998–2004) were followed-up in 2007. Follow-up efforts were extensive for a subcohort and minimal for the remainder (nonsubcohort). Thus, 596 subcohort and 418 nonsubcohort women who delivered at term participated. Offspring were categorized as small-, appropriate-, or large-for-gestational-age (SGA, AGA, and LGA, respectively) based on gender and gestational age-specific birth weight z-scores (BWz). At follow-up, women recalled pregnancy LTPA and were classified as inactive, insufficiently active or meeting LTPA recommendations. Linear, logistic, and quantile regression analyses were conducted separately by subcohort status.


Meeting LTPA recommendations decreased odds of LGA significantly among the nonsubcohort (aOR = 0.30, 95% CI: 0.14–0.64) and nonsignificantly among the subcohort (aOR = 0.68, 95% CI: 0.34–1.34). In quantile regression, meeting LTPA recommendations reduced BWz among the upper quantiles in the nonsubcohort.


LTPA during pregnancy lowered odds of LGA and reduced BWz among the upper quantiles, without shifting the entire distribution. LTPA during pregnancy may be useful for reducing risks of large fetal size.

Restricted access

Gregory J. Welk

correspond to the individual segments captured by the YAP items, and these estimates were matched by ID with the students’ YAP scores. Separate prediction equations were then developed for each of the individual YAP items using quantile regression models ( Saint-Maurice & Welk, 2015 ). The developed

Restricted access

Sarah G. Sanders, Elizabeth Yakes Jimenez, Natalie H. Cole, Alena Kuhlemeier, Grace L. McCauley, M. Lee Van Horn, and Alberta S. Kong

obesity: a quantile regression analysis . Med Sci Sports Exerc . 2017 ; 49 ( 3 ): 466 – 473 . PubMed ID: 27755284 doi:10.1249/MSS.0000000000001129 27755284 10.1249/MSS.0000000000001129 28. Hay J , Maximova K , Durksen A , et al . Physical activity intensity and cardiometabolic risk in youth

Restricted access

Toben F. Nelson, Richard F. MacLehose, Cynthia Davey, Peter Rode, and Marilyn S. Nanney

. 2003 ; 57 ( 1 ): 29 – 35 . PubMed doi:10.1136/jech.57.1.29 10.1136/jech.57.1.29 29. Chen J , Vargas-Bustamante A , Mortensen K , Thomas SB . Using quantile regression to examine health care expenditures during the Great Recession . Health Serv Res . 2014 ; 49 ( 2 ): 705 – 730 . PubMed doi

Restricted access

Anthony Krautmann, Peter von Allmen, and Stephen J.K. Walters

rerunning the model as a quantile regression, they found a few agent-specific effects. For example, some agents seem particularly good at negotiating on behalf of high-performing players, whereas others fare better with players expected to have a smaller impact on team performance. Previous studies by Mason