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Estela Farías-Torbidoni, Demir Barić and Sebastià Mas-Alòs

sociodemographic and trip descriptors on the group membership, a series of logistic regression analyses were performed. Independent nominal variables were recoded as dummy variables. The independent variables entered into each model were evaluated for possible collinearity; the tolerance and variation inflation

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You Fu and Ryan D. Burns

the number of comparisons) for the primary analyses to adjust for potential type I error inflation. All analyses were carried out using STATA v14.0 statistical software package (StataCorp LLC, College Station, TX). Results Girls in this sample were heavier (mean difference = 4.6 kg, P  = .02) and had

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Meera Sreedhara, Karin Valentine Goins, Christine Frisard, Milagros C. Rosal and Stephenie C. Lemon

variance inflation factors (>10). Model fit was assessed using the Hosmer–Lemeshow test. We used Stata for all analyses (version 13.1; StataCorp LP, College Station, TX). Results The survey response rate was 30.2% (209/693). Of the LHDs that completed the survey, we excluded LHDs missing data on CHIP

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Ali M. McManus, Nathan R. Sletten and Daniel J. Green

obtained, baseline SFA diameter and blood flow velocity were continuously measured for 1-minute prior to cuff inflation. The cuff was inflated to 50 mm Hg above resting systolic blood pressure for 5 minutes, with measurement resuming 30 seconds prior to cuff deflation and continuing for 5 minutes postcuff

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Gabriel Lozano-Berges, Ángel Matute-Llorente, Alejandro Gómez-Bruton, Alejandro González-Agüero, Germán Vicente-Rodríguez and José A. Casajús

distribution by the Kolmogorov–Smirnov test. Tanner status differences between genders were assessed using the chi-square test. Paired t tests were performed to analyze differences in %BF between equations and DXA. The potential inflation of multiple comparisons was controlled by Bonferroni correction, and

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Pak-Kwong Chung and Ka-Man Leung

score ± 4.0) were identified. All items’ skewness and kurtosis and their variance inflation factors were less than four (−.63–1.14) and 10 (1.38–4.89), respectively, indicating that the data distribution was univariate normal and no multicollinearity was identified. However, in Study 2, three

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David R. Hooper, William J. Kraemer, Rebecca L. Stearns, Brian R. Kupchak, Brittanie M. Volk, William H. DuPont, Carl M. Maresh and Douglas J. Casa

transformation. In these cases, the transformed data were used for statistical comparisons. A repeated-measures analysis of variance was conducted on the testosterone and cortisol concentrations with a Bonferroni correction factor to control for alpha inflation. Correlations between subject age, body composition

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Nicola Giovanelli, Lea Biasutti, Desy Salvadego, Hailu K. Alemayehu, Bruno Grassi and Stefano Lazzer

inflation (at 300–350 mm Hg), maintained until Δ[deoxy(Hb+Mb)] reached a plateau. Δ[deoxy(Hb+Mb)] kinetics during the incremental tests were fitted by a sigmoid function, as previously presented by other authors and by our group. 14 , 18 Then, we calculated mean values of cardiorespiratory and muscle

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Jeffrey J. Milroy, Stephen Hebard, Emily Kroshus and David L. Wyrick

subscales, variance inflation factors (VIFs) were examined. The threshold for identifying collinearity between CAAS constructs was a VIF greater than 10 ( Belsley, Kuh, & Welsch, 1980 ). Next, binomial logistic regression was used to assess if coach-athlete attachment subscales significantly contribute to

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Colin D. McLaren and Kevin S. Spink

conflict and, to a lesser degree, with information-exchange communication (see Table  1 for correlations). As such, a decision was made to remove this communication type from further analyses to reduce redundancy in the regression equation and avoid the artificial inflation of standard errors ( Tabachnick