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Todd C. Wehner and Douglas V. Shaw

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Richard P. Marini

Experiments with factorial arrangements of treatments plus one or more other treatment(s) are sometimes analyzed with a one-way analysis of variance (ANOVA) and means are separated with a multiple comparison. A set of single degree-of-freedom contrasts in a one-way ANOVA, provides formal tests for main effects and interactions. Data from a 2 × 3 factorial experiment that also contained a control were analyzed with a one-way ANOVA with a multiple comparison. Results from this analysis were compared to results obtained from a two-way ANOVA, a one-way ANOVA with pre-planned contrasts, a two-way ANOVA with least squares means comparisons obtained with SAS/general linear models procedure, and a regression model with an indicator variable and random blocks obtained with SAS/Mixed procedure. Results and interpretation differed depending on how the data were analyzed and these differences are discussed.

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H.P. Piepho, E.R. Williams, and M. Fleck

Many experiments involve a complex treatment structure, and it is not always immediately obvious how such experiments should be analysed. This paper shows by way of three examples how a suitable linear model can be formulated that provides a meaningful analysis of variance table and allows mean comparisons of interest to be obtained in a straightforward manner. Possible advantages of this approach compared to the use of linear contrasts are discussed. It is concluded that a well-chosen model can often considerably simplify the analysis and lead to useful statistical inferences. The approach advocated in this paper is going to be strongest when there is good design structure present.

Open access

Julie H. Campbell and Benjamin L. Campbell

( Flagg et al., 2013 ; Wolfe, 2013 ; Zepeda, 2009 ). Table 1. Descriptive statistics of the sample of Connecticut survey respondents who had purchased plants as determined by a 2016 survey of Connecticut residents. Analysis of variance with post hoc

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Sogo Nishio, Masahiko Yamada, Norio Takada, Hidenori Kato, Noriyuki Onoue, Yutaka Sawamura, and Toshihiro Saito

harvest from each tree by means of one-way analysis of variance (ANOVA). The phenotypic value of NW ( P 1 ijk ) for the k th nut of the j th tree of the i th genotype (cultivar/selection) was expressed using the following model: where the subscript 1

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Andrea Dravigne, Tina Marie Waliczek, R.D. Lineberger, and J.M. Zajicek

” (all further listings of window views assume an exterior green space view). The groups were then compared using analysis of variance (ANOVA) tests to ensure that the groups were similar demographically and suitable for comparison. Because confounding

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Jim C. Cervantes-Flores, G. Craig Yencho, Kenneth V. Pecota, Bryon Sosinski, and Robert O.M. Mwanga

those described by Hussey and Barker (1973) , and there is the added benefit of nontoxicity. The counts of EM per root system were standardized by logarithmic transformation [log (x)] and analysis of variance (ANOVA) using SAS (version 9.1; SAS

Open access

Seon-Ok Kim, Su-Been Pyun, and Sin-Ae Park

using the ratio of power in the 4–8 Hz band to power in the 12–15 Hz band. One-way analysis of variance and Duncan’s multiple range test were performed using SPSS (version 25 for Windows; IBM, Armonk, NY) to compare the EEG and subjective evaluation

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Aime J. Sommerfeld, Amy L. McFarland, Tina M. Waliczek, and Jayne M. Zajicek

. The data were saved into an Excel spreadsheet and then transferred and analyzed using SPSS (Version 11.5). Statistical procedures included descriptive statistics, Pearson's product-moment correlations, and multivariate analysis of variance (MANOVA

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Chen-Yu Lin, Kan-Shu Chen, Hsuan-Ping Chen, Hsiang-I Lee, and Ching-Hsiang Hsieh

30 °C ( Figs. 1 and 2 ). Analysis of variance on curd development revealed that temperature, cultivar, and interaction showed a significant effect on the apex at the phases of curd initiation and curd initial development. Apical growth at 18 °C