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Tony Adebero, Brandon John McKinlay, Alexandros Theocharidis, Zach Root, Andrea R. Josse, Panagiota Klentrou and Bareket Falk

correlation analyses were used to assess correlations between serum and salivary measures in the pooled sample of boys or men and of preexercise and postexercise values. Statistical significance was accepted at P  < .05, which was conducted using SPSS for Windows (version 25; SPSS Inc, Chicago, IL). All

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Hande Guney-Deniz, Gulcan Harput, Ugur Toprak and Irem Duzgun

with scapular positioning. To our knowledge, there was no study in the literature that investigated the effect of active scapula retraction on AHD and its relation to shoulder and scapular muscle activation in asymptomatic individuals. Therefore, the aim of this study was to investigate the correlation

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Serkan Usgu, Günseli Usgu, Fatma Uygur and Yavuz Yakut

calculated and recorded for the injured limb in this study. Statistical Analysis The descriptive statistics were calculated using percentages, means, standard deviations (SD), and ranges. The Spearman rank correlation test and intraclass correlation coefficient (ICC 2,1 ) were used for reliability testing

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Robert MacKenzie, Linda Monaghan, Robert A. Masson, Alice K. Werner, Tansinee S. Caprez, Lynsey Johnston and Ole J. Kemi

, with climbing training continuing at will. Pretests and posttests including climbing ability were measured as described above. Statistics Climbing ability was set as the dependent variable, whereas other variables were treated as independent. Pearson correlation coefficients assessed the relationships

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Neal R. Glaviano and Susan Saliba

daily activities. The score is calculated by taking the summed score, divided by 70 (maximum potential points), and multiplied by 100. The ADLS has been shown to have excellent test–retest reliability (interclass correlation coefficient [ICC] = .93–.99) and a low measurement error of 8.3% when assessed

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Rasool Bagheri, Ismail Ebrahimi Takamjani, Mohammad R. Pourahmadi, Elham Jannati, Sayyed H. Fazeli, Rozita Hedayati and Mahmood Akbari

, the sample size was estimated to compare the variables between healthy and NCLBP groups. In the second part, the sample size was calculated to examine the correlation between the variables of interest. For the first part, the sample size was calculated according to a previous similar study by Steele

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Saurabh Sharma and M. Ejaz Hussain

slow to change their clinical characteristic in 2 days. Statistical Analyses The statistical analysis was performed with SPSS 21.0 version (SPSS Inc., Chicago, IL). A level of p  < .05 was considered statistically significant. Pearson correlation coefficient (convergent validity), exploratory factor

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Mark Kramer, Mark Watson, Rosa Du Randt and Robert W. Pettitt

from a relevant AOT), and CS represents the average speed in the final 30 seconds of an AOT. Statistical Analyses Descriptive data are reported as mean (SD). To evaluate the consistency of measurements between protocols, we utilized the correlation coefficient ( r ) and the standard error of the

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Stef Feijen, Angela Tate, Kevin Kuppens, Thomas Struyf, Anke Claes and Filip Struyf

size was determined using estimates for correlation, r (N = 22, effect size = .50, power = .80) and 2-way analysis of variance, F (N = 17, effect size = .50, power = .80, df = 1). 10 , 11 All variables were tested for normality using the Shapiro–Wilk test ( P  > .05). Intraclass correlation

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Thiago S. Duarte, Danilo L. Alves, Danilo R. Coimbra, Bernardo Miloski, João C. Bouzas Marins and Maurício G. Bara Filho

(OITL), mainly represented by the model based on the intensity zones of the heart rate (HR). 17 – 19 Separately, these measurements indicated a strong correlation with measures of external load 12 , 19 and performance in team sports. 5 , 6 However, the correlation between the internal load