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Li-Chun Huang

search activities and purchases J. Environ. Hort. 26 4 1061 1068 Bentler, P.M. Bonett, D.G. 1980 Significance tests and goodness-of-fit in the analysis of covariance structures Psychol. Bull. 88 588 606 Bollen, K.A. 1989 Structural equations with latent

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Waltram Ravelombola, Ainong Shi, Jun Qin, Yuejin Weng, Gehendra Bhattarai, Bazgha Zia, Wei Zhou, and Beiquan Mou

ANOVA with repeated measures was that of corresponding to the lowest Bias-Corrected Small Sample Akaike Information Criterion (AICC) as described by Littell et al. (2000) . Types of covariance structure from which the selection was done were

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Mary Helen Ferguson, Christopher A. Clark, and Barbara J. Smith

together, likelihood ratio chi-square tests were done to determine if a better fit resulted from using combined or separate variances by plant infection status or by year and if an autoregressive covariance structure resulted in a better fit than the

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Syuan-You Lin and Shinsuke Agehara

based on the smallest AICc. Budbreak and cumulative flower count data were analyzed using a repeated measures analysis because they were collected repeatedly from the same experimental unit. To identify the appropriate covariance structure, model

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Tomas N. Hasing, Luis F. Osorio, and Vance M. Whitaker

, average, and unstable) and used the same variance–covariance structure of the model in Eq. [1]. Heritability estimation. Broad-sense ( H 2 ) and narrow-sense ( h 2 ) heritabilities of regression slopes were estimated for the first set of seedling genotypes

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Richard J. Heerema, Dawn VanLeeuwen, Rolston St. Hilaire, Vince P. Gutschick, and Bethany Cook

-measures analysis of variance was conducted with tree N status (low, medium, high) as the treatment factor and shoot fruiting status (fruiting, non-fruiting) as the repeated factor. Either a compound symmetric or an unstructured covariance structure was fit to

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Filippo Rimi, Stefano Macolino, Bernd Leinauer, and Umberto Ziliotto

reach 80% of green cover were statistically analyzed using a repeated measures analysis of variance (ANOVA) with SAS Proc Mixed (version 9.2; SAS Institute, Cary, NC). A compound symmetry covariance structure resulted in the best fit for the data (lowest

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Vance M. Whitaker, Tomas Hasing, Craig K. Chandler, Anne Plotto, and Elizabeth Baldwin

first-order autoregressive covariance structure. The full model included genotype, location, block (nested within locations), month, and all possible interactions. Like with physical traits, specific analyses within locations and/or months were performed

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George C.J. Fernandez

experiment requires two random error terms for main plots and subplots. Repeated measurements taken at different points in time or space are correlated, which may be accounted for by a mixed model with an appropriate variance–covariance structure. Experiments

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Linsey A. Newton and Erik S. Runkle

repeated measures, with an autoregressive variance/covariance structure with heterogeneous variances. Differences were declared significant at P ≤ 0.05. Mean separation with Tukey's honestly significant difference test at P ≤ 0.05 was used to analyze