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Li-Chun Huang and Yen-Chun Lin

satisfactory level, being a Cronbach’s α higher than 0.70, the minimum acceptable level for scale reliability ( Hair et al., 2010 ). Multinomial logistic regression analysis was applied to investigate the effects of the independent variables on the likelihood

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Yuto Kitamura, Hisayo Yamane, Akira Yukimori, Hiroyoshi Shimo, Koji Numaguchi, and Ryutaro Tao

each treated tree was estimated using the following logistic regression curve with threshold and inflection points set to 100% and 50% (i.e., blooming percentage), respectively: where d c , f ( d c ), α 1 , and α 2 correspond to the chilling

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Kristen R. Hladun and Lynn S. Adler

averaged within plant to use plant as the unit of replication. Logistic regression was used to predict the probability of fruit set, including the continuous variable pollination date as a covariate. Because fruit set was relatively rare, plants that set

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Tracy A. Boyer, D. Harshanee W. Jayasekera, and Justin Q. Moss

familiarity with the landscaping options and to reduce hypothetical bias by surveying actual decision-makers familiar with the landscaping budget. Table 1. Summary statistics of explanatory variables used in logistic regression analyses to determine the

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Yen-Chun Lai and Li-Chun Huang

profile the sample. Multinomial logistic regression analysis was used to evaluate the influence of the development stage, affection, and satisfaction level of a romantic relationship on the purchase decision of whether to buy fresh flowers as a romantic

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Elizabeth A. Gall, B. Rosie Lerner, and Kathryn S. Orvis

magnitude of the effect (whether one would expect to see that relationship in the population). Ordinal logistic regression was used to construct a predictive model of total volunteer hours per month with the following items as independent variables

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Carolina A. Torres, Omar Hernandez, Maria A. Moya-León, Ivan Razmilic, and David R. Rudell

<1% starting at 60 d. There was no “stain” on Exposed or Shaded fruit. By contrast, symptoms started to appear beginning at 45 d in Mod and Sev sunburned fruit, and 75 d in the Mild category ( Fig. 2 ). Logistic regressions using sunburn categories at

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Karl Guillard, Richard J.M. Fitzpatrick, and Holly Burdett

was not included in either logistic regression. Both models passed the Hosmer–Lemeshow goodness-of-fit test ( P > 0.05), indicating a good fit of the data to the model. Results and Discussion Producer-subjective ratings of sod strength were

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Arthur Villordon, Julio Solis, Don LaBonte, and Christopher Clark

, receiver operating characteristic (ROC) analysis, and performance relative to a baseline model (logistic regression). Fig. 4. Alpha-level Bayesian belief network structures evaluated for prototype beta-level model development of the relationship

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Darren J. Hayes and Bryan J. Peterson

statistical software R version 3.3.2 ( R Core Team, 2016 ). Propagation success was analyzed via logistic regression, with overall effects of treatments on propagation success analyzed by the Wald test conducted using the aod version 1.1-32 ( Lesnoff and