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José-Antonio Cecchini, Antonio Méndez-Giménez and Beatriz Sánchez-Martínez

imputation process, and its estimates are the least biased ( Schafer & Graham, 2002 ). Measurements and Instruments Types of motivation The Perceived Locus of Causality Questionnaire ( Goudas, Biddle, & Fox, 1994 ) was used; we selected the version adapted and validated in Spanish by Moreno, González

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Zachary Y. Kerr, Andrew E. Lincoln, Shane V. Caswell, David A. Klossner, Nina Walker and Thomas P. Dompier

of each category AE count do not equal total AE count due to rounding error (due to the use of mean imputation values based on all other valid AE data from the same year, division, and event type for missing data). Table 2 Injury Frequencies and Rates With 95% Confidence Intervals (CI) by Season and

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Wonjae Choi and Seungwon Lee

analysis and were substituted by multiple imputation methods. The missing data were imputed by using Fully Conditional Specification algorithm which is an iterative Markov chain Monte Carlo method. Five imputed datasets were generated and then pooled outcomes were used for the intention-to-treat analysis

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Jennifer Brunet, Eva Guérin and Nicolas Speranzini

violation of assumptions using IBM SPSS Statistics software (version 23; IBM Corporation, Armonk, NY) following procedures outlined by Tabachnick and Fidell ( 2007 ). Multiple imputation was performed to impute missing sociodemographic data given the low degree of missingness (< 5%). Four univariate

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Yuri Alberto Freire, Geovani de Araújo Dantas de Macêdo, Rodrigo Alberto Vieira Browne, Luiz Fernando Farias-Junior, Ágnes Denise de Lima Bezerra, Ana Paula Trussardi Fayh, José Cazuza de Farias Júnior, Kevin F. Boreskie, Todd A. Duhamel and Eduardo Caldas Costa

trapezoidal method using the GraphPad Prism (version 6) for Windows (GraphPad Software ® , San Diego, CA). Intention-to-treat principle was used for analyses; that is, data from participants who completed only 1 or 2 experimental sessions were included in the final analysis without data imputation

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Liane S. Lewis, Barnabas Shaw, Srijit Banerjee, Pryscilla Dieguez, James Hernon, Nigel Belshaw and John M. Saxton

were not imputed because imputation has been shown to be flawed in longitudinal studies with a large amount of missing data ( Lane, 2008 ). The mixed model analysis included the following number of participants at each time point: BL: n  = 31, 3 months: n  = 27, 6 months: n  = 22, 9 months: n  = 15

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Guohua Zheng, Xin Zheng, Junzhe Li, Tingjin Duan, Kun Ling, Jing Tao and Lidian Chen

fixed effect and participant as a random variable. The baseline data and comparison group were used as the reference values. A fully unstructured variance–covariance matrix was assumed for the error terms. Missing data were imputed using a multiple imputation method based on a fully conditional

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Victoria McGee and J.D. DeFreese

as a cut-off criterion for acceptability. Descriptive statistics and scale reliabilities were calculated for all study variables at every time point. Missing data from a completed assessment wave were replaced via mean imputation. Multilevel linear modeling (MLM; Singer & Willett, 2003 ) using

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

.J. , & Lipsitz , S.R. ( 2001 ). Multiple imputation in practice: Comparison of software packages for regression models with missing variables . The American Statistician , 55 ( 3 ), 244 – 254 . 10.1198/000313001317098266 Keller , J. , Lamenoise , J.M. , Testa , M. , Golomer , E. , & Rosey , F

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J.D. DeFreese, Travis E. Dorsch and Travis A. Flitton

Cronbach’s α values) were calculated for all study variables. Missing data from participants completing the entire survey were replaced for focal variables with values calculated via mean imputation ( Tabachnick & Fidell, 2013 ). Confirmatory factor analyses were conducted for the adapted measures of sport