Split-Plot Analysis of Variance

2014 ◽  
pp. 71-75
Author(s):  
Richard A. Armstrong ◽  
Anthony C. Hilton
Keyword(s):  
Analysis Of Variance ◽  
Plot Analysis ◽  
Split Plot

Use of a Split-Plot Analysis of Variance Design for Repeated-Measures Fishery Data

Fisheries ◽  
1994 ◽  
Vol 19 (3) ◽  
pp. 14-20 ◽  
Author(s):  
Michael J. Maceina ◽  
Phillip W. Bettoli ◽  
Dennis R. DeVries
Keyword(s):  
Analysis Of Variance ◽  
Repeated Measures ◽  
Variance Design ◽  
Plot Analysis ◽  
Split Plot ◽  
Fishery Data

scholarly journals Microhardness and color monitoring of nanofilled resin composite after bleaching and staining

2014 ◽  
Vol 08 (02) ◽  
pp. 160-165 ◽  
Author(s):  
Isabel Cristina G. Bandeira de Andrade ◽  
Roberta Tarkany Basting ◽  
José Augusto Rodrigues ◽  
Flávia Lucisano Botelho do Amaral ◽  
Cecilia Pedroso Turssi ◽  
...  
Keyword(s):  
Hydrogen Peroxide ◽  
Analysis Of Variance ◽  
Red Wine ◽  
Light Emission ◽  
Resin Composite ◽  
Distilled Water ◽  
Bleaching Agent ◽  
Carbamide Peroxide ◽  
Split Plot ◽  
Plot Design

ABSTRACT Objectives: The present study aimed to investigate the effect of staining solutions on microhardness and shade changes of a nanofilled resin composite, which had been previously in contact with bleaching agents. Materials and Methods: A total of 135 disk-shaped specimens (10 mm × 2 mm) were fabricated with a nanofilled resin (Filtek Supreme) and photocured with a Light Emission Diode (LED) unit and then allocated into three groups to be bleached with 10% or 16% carbamide peroxide (CP) bleaching agents or a 35% hydrogen peroxide (HP) product. Following bleaching, specimens within each group were subdivided into three groups to be immersed in coffee, red wine or distilled water. Microhardness and color were monitored at baseline, after bleaching and after staining. Results: Analysis of variance for split-plot design showed lower microhardness values when the composite had been in contact with HP (P < 0.0001). The specimens immersed in red wine and coffee provided lower microhardness values than those immersed in distilled water, regardless of the bleaching agent to which the composites were previously exposed. Kruskal Wallis and Dunn tests demonstrated that the composite was lighter after bleaching with a 35% HP agent (P < 0.0500). Conclusion: The composite was darker as a result of being immersed either in red wine or coffee, regardless of the bleaching agent.

scholarly journals On a new approach to the analysis of variance for experiments with orthogonal block structure. IV. Experiments in split-plot designs

2020 ◽  
Vol 57 (2) ◽  
pp. 151-175
Author(s):  
Tadeusz Caliński ◽  
Agnieszka Łacka ◽  
Idzi Siatkowski
Keyword(s):  
Experimental Data ◽  
Hypothesis Testing ◽  
Analysis Of Variance ◽  
Block Structure ◽  
Practical Application ◽  
Simple Manner ◽  
New Approach ◽  
Testing Procedures ◽  
Split Plot

SummaryThis paper provides estimation and hypothesis testing procedures for experiments in split-plot designs. These experiments have been shown to have a convenient orthogonal block structure when properly randomized. Due to this property, the analysis of experimental data can be carried out in a relatively simple manner. Relevant simplification procedures are indicated. According to the adopted approach, the analysis of variance and hypothesis testing procedures can be performed directly, rather than by combining the results of analyses based on some stratum submodels. The practical application of the presented theory is illustrated by examples of real experiments in appropriate split-plot designs. The present paper is the fourth in the planned series of publications on the analysis of experiments with orthogonal block structure.

scholarly journals Cabbage Seedpod Weevil Control on Winter Canola, 1996

1998 ◽  
Vol 23 (1) ◽  
pp. 186-187
Author(s):  
J. P. McCaffrey ◽  
B. L. Harmon
Keyword(s):  
Analysis Of Variance ◽  
Methyl Parathion ◽  
Ambient Air ◽  
Winter Canola ◽  
Split Plot ◽  
Small Plot ◽  
Cabbage Seedpod Weevil ◽  
Plot Design

Abstract Plots, 3.5 X 12 ft, arranged in a split-plot design with each chem-ical treatment replicated 3 times, and each of 4 genotypes replicated twice within each treatment strip, were planted at Moscow, ID on 20 Aug, 1995 at 9.5 lb/acre using a small-plot, cone seeder. Capture 2 EC and methyl parathion 4 E were applied 5 Jun with a CO2-pressurized tractor-mounted sprayer equipped with 80° fan nozzles on an 8.3-ft boom that delivered 20 gpa at 30 psi. At the time of treatment, wind conditions were calm (&lt;5 mph), and ambient air tem-perature was above 60°F. Plots were sampled for adult CSW 2 before treatment and 2 d after treatment by dislodging them into a 5-gal plastic bucket with a beat of a hand at each end of a plot. To determine the number of exit holes, 10 pods were removed from 10 racemes from each side of each plot on 17 and 18 Jul. Plots were harvested 15 Aug with a small-plot combine (4.6 ft header). All data were subjected to analysis of variance.

scholarly journals Repeated measures in randomized block and split-plot experiments

1993 ◽  
Vol 23 (4) ◽  
pp. 625-639 ◽  
Author(s):  
M.L. Gumpertz ◽  
C. Brownie
Keyword(s):  
Multivariate Analysis ◽  
Analysis Of Variance ◽  
Loblolly Pine ◽  
Repeated Measures ◽  
Univariate Analysis ◽  
Complete Analysis ◽  
Phosphorus Fertilization ◽  
Multivariate Analysis Of Variance ◽  
Repeated Measures Data ◽  
Split Plot

Randomized block and split-plot designs are among the most commonly used experimental designs in forest research. Measurements for plots in a block (or subplots in a whole plot) are correlated with each other, and these correlations must be taken into account when analyzing repeated-measures data from blocked designs. The analysis is similar to repeated-measures analysis for a completely randomized design, but test statistics must allow for random block × time effects, and standard errors for treatment means must also incorporate block to block variation and variation among plots within a block. Two types of statistical analysis are often recommended for repeated-measures data: analysis of contrasts of the repeated factor and multivariate analysis of variance. A complete analysis of repeated measures should usually contain both of these components, just as in univariate analysis of variance it is often necessary to decompose the main effects into single degree of freedom contrasts to answer the research objectives. We demonstrate the multivariate analysis of variance and the analysis of contrasts in detail for two experiments. In addition, estimation of coefficients assuming a polynomial growth curve is discussed in detail for one of these experiments. The first experiment, a randomized complete block design, is a forest nutrition study of the long-term effects of midrotation nitrogen and phosphorus fertilization on loblolly pine (Pinustaeda L.); the second experiment, a split-plot design, is an air-pollution study of the effects of ozone and acid precipitation on loblolly pine growth.

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