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Greg Wood, Samuel J. Vine, Johnny Parr and Mark R. Wilson

same location on the opposite side of the goal). Players shot using an indoor Mitre Cyclone football (Manchester, UK) of standard inflation. Shot location was recorded using a Panasonic SDR-S26 (60 Hz; Osaka, Japan) camcorder that was located 1 m to the right of the penalty spot. Figure 2 —Goal

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Rebekka Pomiersky, Bastian Abel, Christian Werner, André Lacroix, Klaus Pfeiffer, Martina Schäufele and Klaus Hauer

). Model 2: Δ PAQE total at T3 − PAQE total at T1 for total study sample ( N  = 96). PAQE = Physical Activity Questionnaire for the Elderly; β = standardized regression coefficient; VIF = Variance inflation factor; TUG = Timed Up and Go; CIRS = Cumulative Illness Rating Scale; MMSE = Mini-Mental State

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

variables, taking the variance for the Level 1 (repeated measures), Level 2 (students), Level 3 (classrooms), Level 4 (teachers), and Level 5 (schools). We selected multilevel modeling because it is recommended for the analysis of repeated measurements and reduces the risk of inflation of Type I errors. It

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Maurice Vergeer and Leon Mulder

correlated (e.g., minutes, goals and assists, position in the field), checks for multicollinearity were performed. The variance inflation factors (VIF; Cohen, Cohen, West, & Aiken, 2002 ) for both models are below the critical value of 10 (maximum VIF adoption model = 1.964, maximum VIF followers model = 4

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Avelina C. Padin, Charles F. Emery, Michael Vasey and Janice K. Kiecolt-Glaser

met. Specifically, visual inspection of residual plots of regression models indicated that the regression assumption of homoscedasticity was met. Calculation of the variance inflation factor and tolerance indicated that multicollinearity was not present. Results Attitudes and Average PA Duration

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Tsz Lun (Alan) Chu, Tao Zhang, Katherine T. Thomas, Xiaoxia Zhang and Xiangli Gu

Endurance Run. * p  < .05. ** p  < .01. *** p  < .001. All assumptions for correct specification of the regression models were met, and no multicollinearity was observed with the diagnostics of variance inflation factors (<10), tolerance (>.10), and condition numbers (κ < 30). It is important to note that

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Chien-Chih Chou, Kuan-Chou Chen, Mei-Yao Huang, Hsin-Yu Tu and Chung-Ju Huang

significant interaction effects that were identified, whereas multiple comparisons were used to follow-up on any significant main effects. To control for experiment-wise inflation of α, additional Bonferroni adjustments were made. Small to moderate ESs were observed for each of the EF domains of interest (0

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Beth A. Cianfrone, Jessica R. Braunstein-Minkove and Alyssa L. Tavormina

) significantly predicted number of tickets purchased. Table 4 Predictors of Number of Tickets Sold Variable B SE β p Variance inflation factor Constant 300.56 197.57   .135   Number of games/events offered 18.78 7.94 .288 .024* 1.19 Number of e-mails sent 33.04 6.47 .616 .000*** 1.13 Ticket cost of game/event −2

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Leilani A. Madrigal, Vincenzo Roma, Todd Caze, Arthur Maerlender and Debra Hope

comparisons with the Bonferonni correction to correct for alpha inflation (e.g.,  p  <.003). The SAS-2 total score and subscales were substantially correlated with anxiety sensitivity, fear of negative evaluation, intolerance of uncertainty, and negative affect in the expected direction as evidence for

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Stéphanie Girard, Jérôme St-Amand and Roch Chouinard

expectation–maximization algorithm available in Mplus (version 7.4; Muthen & Muthen, Los Angeles, CA) was applied ( Little & Rubin, 2002 ). Multicollinearity testing gave acceptable values: tolerance was above .2, and variance inflation factor was below 1 ( Field, 2009 ). All variables presented acceptable