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Byron Lai, Katie Cederberg, Kerri A. Vanderbom, C. Scott Bickel, James H. Rimmer and Robert W. Motl

explore and describe the demographic and clinical characteristics of adults with neurologic disabilities who were enrolled in exercise trials and determine if the samples, and ultimately study results, may generalize to the broader population of individuals within each disability condition. Methods This

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Viviene A. Temple, P. Lynn Purves, Robyn Misovic, Coral J. Lewis and Carrie DeBoer

Many children with disabling conditions do not acquire the skills to successfully ride a 2-wheeled bicycle. The aim was to describe cycling patterns before and after an innovative learn-to-ride bike camp and factors that facilitate or hinder the generalization of skills developed at camp to home. Parents and children participated in semistructured interviews 3–4 mo postcamp. Transcripts were examined deductively for participation and contextual influences using a template of codes approach. None of the children were successfully riding a 2-wheeled bicycle before camp. Two patterns of participation were evident from narrative descriptions of postcamp riding: “riders” and “not there yet.” Major facilitating factors were the camp itself, the interaction between the camp and the health service, and continued parent involvement. The program transferred well to home for children who were riding independently on the last day of camp. Ongoing support is needed for children “not there yet.”

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Amador García-Ramos, Guy Gregory Haff, Francisco Luis Pestaña-Melero, Alejandro Pérez-Castilla, Francisco Javier Rojas, Carlos Balsalobre-Fernández and Slobodan Jaric

variety of resistance training exercises. 6 , 14 – 16 The load–velocity relationship of a given exercise has also proven to be very stable regardless of the 1RM value of the subject. 6 , 17 These results have encouraged researchers to propose a use of “generalized group equations” for different basic

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Stephen Crowcroft, Katie Slattery, Erin McCleave and Aaron J. Coutts

assessed for their model fit using generalized estimating equations (GEE) and then for their diagnostic accuracy from receiver operating characteristic curve analysis. Athlete-Monitoring Variables Subjective self-report measures recorded in this study included perceived fatigue rating (1 = much worse than

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Ross Wadey, Kylie Roy-Davis, Lynne Evans, Karen Howells, Jade Salim and Ceri Diss

vivid and compelling example extracts ( Braun & Clarke, 2006 ). However, before we submitted for publication, external reflections on the findings were sought to enhance the study’s generalizability from two colleagues who were well versed in the growth-following-adversity literature (i.e., fourth and

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Javier Raya-González, Fabio Yuzo Nakamura, Daniel Castillo, Javier Yanci and Maurizio Fanchini

prospective careers. Hence replication of previous studies 13 , 14 using a sample of young elite soccer players is necessary to verify the generalizability of their findings. Considering the aforementioned evidence and due to the high physiological stress produced by competitive matches, 12 the load

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Brendan H. Lazarus, William G. Hopkins, Andrew M. Stewart and Robert J. Aughey

, similar, heavier, and heaviest; and shortest, shorter, similar, taller, and tallest. Statistical Analysis The logistic-regression version of the generalized mixed linear model (Proc Glimmix) in the Statistical Analysis System (version 9.4, SAS Institute, Cary, NC) was used to estimate the effect of each

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Levi Heimans, Wouter R. Dijkshoorn, Marco J.M. Hoozemans and Jos J. de Koning

position, the drag fraction was estimated using generalized estimation equations (GEE), a regression analysis technique that accounts for the dependency of repeated measurements. 22 For all 3 drafting positions, a regression equation using GEE was established with the Ap of the drafter and the Ap of the

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Fergus O’Connor, Heidi R. Thornton, Dean Ritchie, Jay Anderson, Lindsay Bull, Alex Rigby, Zane Leonard, Steven Stern and Jonathan D. Bartlett

were developed to assess the mean difference between the absolute and relative speed thresholds. To assess the relationship between risk of injury and various individual workload exposure factors, logistic generalized additive models (GAMs) were fit. GAMs allow for the dependence between injury risk

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Teun van Erp, Marco Hoozemans, Carl Foster and Jos J. de Koning

, and thus, excluding the middle group enhances contrast in the analysis. Linear regression analyses were used to investigate whether training intensity (low or high) affects the association between kJ spent and the various other TLs (sRPE, luTRIMP, and TSS). Generalized estimating equations with an