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Alex J. Benson and Mark Eys

) .54 (.07) .04 (.05) .03 (.04) .75 (.04)  CC6 −.11 (.11) .13 (.19) .37 (.14) − .20 (.07) .03 (.06) .83 (.06)  CC7 .02 (.14) .03 (.19) .47 (.11) −.11 (.08) −.04 (.05) .83 (.05) Factor correlations   Factor   SI CC   SI CC  SER   .47 .50   .64 .57  SI     .27     .33  CC             Note. λ

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Aurora de Fátima G.C. Mafra Cabral, Marcelo Medeiros Pinheiro, Charlles H.M. Castro, Marco Túlio De Mello, Sérgio Tufik and Vera Lúcia Szejnfeld

et al., 2008 ). A sample size of 100 women was defined to predict a significant correlation above 0.5, with 90% power or higher. Descriptive statistics to characterize the sample were used, with average and standard deviation for the quantitative variables and proportions for the qualitative

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Frazer Atkinson, Sandra E. Short and Jeffrey Martin

coefficients for all subscales of the CES and CEQS also showed acceptable internal consistency as they were above the minimum .70 threshold proposed by Nunnally and Bernstein ( 1994 ). The plethora of positive and moderate to large correlations (see Table  2 ) among the team- and coach-efficacy subscales are

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Hanan Khalil, Mahmoud A. Alomari, Omar Khabour, Aya Al-Hieshan and Jawad A. Bajwa

examined between the low and high physical capacity groups using the independent-sample Student's t test. Relationships between serum BDNF and cognitive function were firstly evaluated in the whole PD sample (n = 29), then separately in each of the low and high physical capacity groups. Correlation

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Danielle Nesbitt, Sergio Molina, Ryan Sacko, Leah E. Robinson, Ali Brian and David Stodden

were calculated and those frequency percentages were plotted against chronological age ( Roberton et al., 1980 ) to determine the developmental trajectories of each component. Next, Spearman’s Rho correlations were calculated to examine the associations between STS time and the three STS components of

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Maike Tietjens, Dennis Dreiskaemper, Till Utesch, Nadja Schott, Lisa M. Barnett and Trina Hinkley

, 2017 ). Additionally, sex, age, height, and weight were recorded. Analyses were conducted using SPSS 23. Spearman correlations were performed to test the relations between the given constructs. To test face validity, the interviewer reported (a) whether children had problems in responding after each

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Levi Frehlich, Christine Friedenreich, Alberto Nettel-Aguirre, Jasper Schipperijn and Gavin R. McCormack

-intensity physical activity, the day-to-day intraclass correlation for accelerometer counts estimated for at least three valid consecutive days was .80 ( Supplementary Material [available online]). ActiGraph ® wGT3X-BT is a tri-axial accelerometer that has been found to be reliable in free-living situations

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Feng-Tzu Chen, Su-Ru Chen, I-Hua Chu, Jen-Hao Liu and Yu-Kai Chang

comparison with Bonferroni corrections, with Greenhouse–Geisser corrections also reported. To determine the relationships between the physical fitness and metacognition measures, we also conducted Pearson product-moment correlations between the difference scores (i.e., the difference between the pre- and the

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Andrea Stewart, Barbara Sternfeld, Brittney S. Lange-Maia, Kelly R. Ylitalo, Alicia Colvin, Carrie A. Karvonen-Gutierrez, Sheila A. Dugan, Robin R. Green and Kelley Pettee Gabriel

of women’s health ( Pettee Gabriel et al., 2009 ). The results from these studies have primarily demonstrated low to moderate correlation or agreement, overall ( Ainsworth, Sternfeld, Richardson, & Jackson, 2000 ; Pettee Gabriel et al., 2009 ). The low-to-moderate relation between measurement

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Laura D. Ellingson, Paul R. Hibbing, Gregory J. Welk, Dana Dailey, Barbara A. Rakel, Leslie J. Crofford, Kathleen A. Sluka and Laura A. Frey-Law

self-report, relationships between the PA outcomes using the four accelerometer processing methods and self-reported activity (IPAQ-SF, MET-min/week) were assessed using Spearman’s correlation coefficient on a subsample of participants with self-report PA data ( n  = 147). Time spent in sedentary