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Samantha M. Ross, Ellen Smit, Joonkoo Yun, Kathleen Bogart, Bridget Hatfield and Samuel W. Logan

/are there: (1) a park or playground, or (2) a recreation center, community center, or boys’ and girls’ club.” Missing data for child’s sex, race, and Hispanic ethnicity were treated using a hot-deck imputation method, while missingness for highest education of the primary adult respondent for household and

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Mindy Patterson, Wanyi Wang and Alexis Ortiz

II. Thus, the data was considered as Missing at Random. Therefore, multiple imputation methods were used to replace incomplete data. Specifically, each missing value was imputed (i.e., filled-in) using linear regression model 5 times to create 5 pseudo-complete datasets. Each dataset was analyzed to

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Samantha M. Gray, Joan Wharf Higgins and Ryan E. Rhodes

qualitative findings according to the sequential explanatory mixed methods design. Quantitative analyses Prior to running any quantitative analyses, the data were evaluated for missingness. As Little’s test was nonsignificant (χ 2  = 0.000, df  = 44, p  = 1.00), the data could undergo multiple imputations

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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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Erika D. Van Dyke, Judy L. Van Raalte, Elizabeth M. Mullin and Britton W. Brewer

particular need for mental focus on the beam ( Bannon, 2016 ). Statistical Analyses Once exclusion criteria were applied, it was found that 16 participants omitted a combined total of 20 items from the self-talk measures. The maximum number of participants missing any single item was two. Mean 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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Kirsi E. Keskinen, Merja Rantakokko, Kimmo Suomi, Taina Rantanen and Erja Portegijs

of education, data were missing for eight participants, and no imputation was conducted. The last change of address was missing for 30 participants, and these values were imputed as the sample average of the time lived in the current home. The intraclass correlation coefficient of PA values between

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Taru Manyanga, Joel D. Barnes, Chalchisa Abdeta, Ade F. Adeniyi, Jasmin Bhawra, Catherine E. Draper, Tarun R. Katapally, Asaduzzaman Khan, Estelle Lambert, Daga Makaza, Vida K. Nyawornota, Reginald Ocansey, Narayan Subedi, Riaz Uddin, Dawn Tladi and Mark S. Tremblay

.1093/bioinformatics/btx364 10.1093/bioinformatics/btx364 45. Kowarik A , Templ M . Imputation with the R Package VIM . J Stat Softw . 2016 ; 74 ( 7 ): 1 – 16 . doi:10.18637/jss.v074.i07 10.18637/jss.v074.i07 46. United Nations . World population prospects 2017 . 2017 . . 47

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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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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