Inference for Variance Components in a Mixed Model for Unbalanced Split Plot Design

2005 ◽  
Vol 34 (1) ◽  
pp. 101-112
Author(s):  
BILGEHAN GÜVEN
Keyword(s):  
Variance Components ◽  
Mixed Model ◽  
Split Plot ◽  
Plot Design

scholarly journals A-Optimal Split Plot Design for Estimating Variance Components

2014 ◽  
Vol 2 (4) ◽  
pp. 235-238
Author(s):  
Nuga O.A ◽  
Amahia G.N ◽  
Fakorede A
Keyword(s):  
Variance Components ◽  
Split Plot ◽  
Plot Design

scholarly journals Nonlinear Split-Plot Design Model in Parameters Estimation using Estimated Generalized Least Square - Maximum Likelihood Estimation

2018 ◽  
Vol 9 (2) ◽  
pp. 65
Author(s):  
Ikwuoche John David ◽  
Osebekwin Ebenenzer Asiribo ◽  
Hussain Garba Dikko
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Variance Components ◽  
Likelihood Estimation ◽  
Parameters Estimation ◽  
Least Square ◽  
Design Model ◽  
Mixed Effect ◽  
Split Plot ◽  
Plot Design

This research aimed to provide a theoretical framework for intrinsically nonlinear models with two additive error terms. To achieve this, an iterative Gauss-Newton via Taylor Series expansion procedures for Estimated Generalized Least Square (EGLS) technique was adopted. This technique was applied in estimating the parameters of an intrinsically nonlinear split-plot design model where the variance components were unknown. The unknown variance components were estimated via Maximum Likelihood Estimation (MLE) method. To achieve the numerical stability in the iterative process of estimating the parameters, Householder QR decomposition was used. The results show that EGLS method presented in this research is available and applicable to estimate linear fixed, random, and mixed-effect models. However, in practical situations, the functional form of the mean in the model is often nonlinear due to the dynamics involved in the system process.

Towards understanding and use of mixed-model analysis of agricultural experiments

2010 ◽  
Vol 90 (5) ◽  
pp. 605-627 ◽  
Author(s):  
R -C. Yang
Keyword(s):  
Random Effects ◽  
Analysis Of Variance ◽  
Mixed Model ◽  
Model Analysis ◽  
General Linear ◽  
Mixed Effect ◽  
Mixed Model Analysis ◽  
Two Samples ◽  
Split Plot ◽  
Plot Design

Despite the presence of both fixed and random effects in most agricultural experiments, many crop researchers have continued use of the conventional analysis of variance (ANOVA) model or general linear model (GLM) that provides a correct analysis only if all the effects are fixed. Ignoring or mistreating random effects may have inadvertently led to inappropriate analyses and thus to dubious conclusions appearing in the scientific literature. The objective of this paper is to provide a tutorial account of the mixed-model methodology and its applications to the analysis of agricultural experiments. The description and discussion on ANOVA vs. mixed-effect models center on the use of PROC GLM vs. PROC MIXED of the SAS® System. This paper points out the need for mixed-model analysis, describes and discusses key new features and properties of mixed-model analysis that would facilitate the understanding and use of PROC MIXED. Additionally, it analyzes and interprets three examples: comparison between two samples, and analyses of randomized complete design and split-plot design. Appendices include SAS code and theory underlying mixed-model analysis which will help gain hands-on experiences and ensure correct interpretation of SAS outputs by PROC MIXED. Such a comparative assessment of GLM vs. MIXED procedures will help to underscore the key advantages of PROC MIXED and to convince GLM users to make a true transition towards the increased and appropriate use of PROC MIXED in agricultural experiments.Key words: Analysis of variance, fixed vs. random effects, general linear models, inference spaces, mixed models, randomized complete block design, split-plot design

Circular dependence in a multiresponse mixed model under a split-plot design

2000 ◽  
Vol 9 (1-3) ◽  
pp. 127-137
Author(s):  
Cinzia Mortarino ◽  
Renato Guseo
Keyword(s):  
Mixed Model ◽  
Split Plot ◽  
Plot Design

Power of Modified Brown-Forsythe and Mixed-Model Approaches in Split-Plot Designs

Methodology ◽  
2017 ◽  
Vol 13 (1) ◽  
pp. 9-22 ◽  
Author(s):  
Pablo Livacic-Rojas ◽  
Guillermo Vallejo ◽  
Paula Fernández ◽  
Ellián Tuero-Herrero
Keyword(s):  
Repeated Measures ◽  
Statistical Power ◽  
Mixed Model ◽  
Covariance Structure ◽  
Simulation Method ◽  
Future Research ◽  
Repeated Measures Design ◽  
Fixed And Random Effects ◽  
Split Plot ◽  
High Level

Abstract. Low precision of the inferences of data analyzed with univariate or multivariate models of the Analysis of Variance (ANOVA) in repeated-measures design is associated to the absence of normality distribution of data, nonspherical covariance structures and free variation of the variance and covariance, the lack of knowledge of the error structure underlying the data, and the wrong choice of covariance structure from different selectors. In this study, levels of statistical power presented the Modified Brown Forsythe (MBF) and two procedures with the Mixed-Model Approaches (the Akaike’s Criterion, the Correctly Identified Model [CIM]) are compared. The data were analyzed using Monte Carlo simulation method with the statistical package SAS 9.2, a split-plot design, and considering six manipulated variables. The results show that the procedures exhibit high statistical power levels for within and interactional effects, and moderate and low levels for the between-groups effects under the different conditions analyzed. For the latter, only the Modified Brown Forsythe shows high level of power mainly for groups with 30 cases and Unstructured (UN) and Autoregressive Heterogeneity (ARH) matrices. For this reason, we recommend using this procedure since it exhibits higher levels of power for all effects and does not require a matrix type that underlies the structure of the data. Future research needs to be done in order to compare the power with corrected selectors using single-level and multilevel designs for fixed and random effects.

Respon Pertumbuhan dan Produksi Kacang Tanah (Arachis hypogaea L.) terhadap Sistem Tanam Alur dan Pemberian Jenis Pupuk

2017 ◽  
Vol 5 (3) ◽  
pp. 342
Author(s):  
Rizal Mahdi Kurniawan ◽  
Heni Purnamawati ◽  
Yudiwanti Wahyu E. K
Keyword(s):  
Arachis Hypogaea ◽  
Arachis Hypogaea L ◽  
Split Plot ◽  
Plot Design

<p><em>Penelitian ini bertujuan untuk mempelajari pengaruh sistem tanam alur dan pemberian jenis pupuk terhadap pertumbuhan dan produksi kacang tanah (Arachis hypogaea L.). Penelitian dilaksanakan di KP Leuwikopo IPB Dramaga, Bogor pada bulan Februari - Juni 2013. Percobaan menggunakan rancangan petak terbagi (Split Plot Design) dengan perlakuan terdiri dari dua faktor, yaitu sistem tanam alur sebagai petak utama dan jenis pupuk sebagai anak petak. Hasil penelitian menunjukkan bahwa perlakuan sistem tanam alur meningkatkan daya hasil pada produktivitas biji kering, produktivitas polong kering, dan bobot kering biji per tanaman lebih baik dibandingkan sistem tanam konvensional. Hal tersebut ditunjukkan dengan perlakuan sistem tanam alur yang memiliki produktivitas 2.93 ton/ha polong kering, sedangkan sistem tanam konvensional sebesar 2.55 ton/ha polong kering. Sistem budidaya kacang tanah pada sistem tanam alur dapat meningkatkan efisiensi tanaman dalam memanfaatkan unsur hara yang telah diberikan baik pupuk organik maupun anorganik, sehingga pertumbuhan dan hasil tanaman kacang tanah menjadi lebih baik. Pemberian jenis pupuk kandang ayam + Dolomit + NPK memberikan respon terhadap pertumbuhan dan  daya hasil rata-rata tanaman yang lebih baik dibandingkan jenis pupuk lainnya.</em></p>

scholarly journals Performance of hybrid rice grown from separated tillers

2019 ◽  
Vol 17 (4) ◽  
pp. 507-513
Author(s):  
FN Kamarum Munira ◽  
Md. Parvez Anwar ◽  
Sabina Yeasmin ◽  
Md. Harun Or Rashid ◽  
Mst Farzana Rahman ◽  
...  
Keyword(s):  
Grain Yield ◽  
Plant Height ◽  
Hybrid Rice ◽  
Rice Variety ◽  
Field Laboratory ◽  
Split Plot ◽  
Rice Seeds ◽  
Four Levels ◽  
Plot Design

The experiment was conducted at the Agronomy Field Laboratory, Bangladesh Agricultural University, Mymensingh during July to November 2016 to investigate the performance of separated tillers of hybrid rice variety Dhani Gold. The experiment comprised three times of tiller transplantation viz. 3, 4 and 5 week aged tiller seedlings and four levels of number of tiller seedlings transplanted hill-1 viz. 2, 3, 4 and 5 tiller seedlings hill-1 laid out in a split plot design with 3 replications. The highest plant height was obtained when 3-week aged tiller seedlings were transplanted at the rate of 3 tiller seedlings hill-1. The highest number of total tillers hill-1 and number of effective tillers hill-1 were found when 3-week aged tiller seedlings were transplanted with 5 tiller seedlings hill-1. The highest grains panicle-1 was obtained when 4-week aged tiller seedlings were transplanted with 5 tiller seedlings hill-1. The highest grain yield was found when 3-week aged tiller seedlings were transplanted with 5 tiller seedlings hill-1. The lowest grain yield was found when 5-week aged tiller seedlings were transplanted with 2 tiller seedlings hill-1 in hybrid rice variety Dhani Gold. Based on the findings of the present study it may be concluded that 3-week old tiller seedlings of Dhani Gold should be transplanted at the rate of 4 or 5 tiller seedlings hill-1 for higher yield. Thus present study confirms the potentiality of growing hybrid rice from separated tillers in case of unavailability of seedlings or to minimize the seed cost of high value hybrid rice seeds. J Bangladesh Agril Univ 17(4): 507–513, 2019

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