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Full-Text Articles in Agriculture
An Example Of Developing Covariates For Problems In Precision Agriculture, D. W. Meek, J. W. Singer
An Example Of Developing Covariates For Problems In Precision Agriculture, D. W. Meek, J. W. Singer
Conference on Applied Statistics in Agriculture
Methodology for precision agriculture is, perhaps, too focused on methods that allow for spatial correlation in the ANOVA error term. While sound inference about differences between local yields can be computed, no understanding of what is driving these differences is achieved. A completely general form for a spatial model can include suitable covariates. Most research in precision agriculture includes gathering a variety of site-specific information. Through the presentation of the analysis of data from a published soybean [Glycine max (L.) Merr.] study, one specific type of covariate is developed - a duration index for soybean canopy light interception over …
Small Sample Power Characteristics Of Generalized Mixed Model Procedures For Binary Repeated Measures Data Using Sas, Matthew Beckman, Walter W. Stroup
Small Sample Power Characteristics Of Generalized Mixed Model Procedures For Binary Repeated Measures Data Using Sas, Matthew Beckman, Walter W. Stroup
Conference on Applied Statistics in Agriculture
Researchers in the agricultural and biological sciences often conduct experiments with repeated measures and categorical response variables. Recent advances in statisticalcomputing have made several options available to analyze data from these experiments. For example, SAS has several procedures based on generalized mixed model theory. These include PROC GENMOD, MIXED, NLMIXED, and the GLIMMIX macro. Inference for these procedures depends on asymptotic theory. While statistics literature contains some information about the small-sample behavior, there is much that remains unknown. This presentation will focus on Bernoulli response variables. Power characteristics are compared via simulation for several scenarios involving relatively small repeated measures …
Alternative Analyses Of Crossover Designs With More Than Two Periods, Carla L. Goad, Dallas E. Johnson
Alternative Analyses Of Crossover Designs With More Than Two Periods, Carla L. Goad, Dallas E. Johnson
Conference on Applied Statistics in Agriculture
A crossover experiment is a special form of a repeated measures experiment. An appropriate analysis of a repeated measures experiment depends on the form of the varian-cecovariance matrix of the repeated measures. Certain forms of this matrix yield valid analysis of variance F -tests while other forms invalidate these tests. In a crossover experiment where analysis of variance tests are invalid, two alternative tests of a linear contrast of the parameters are proposed. In addition to these approximate t-tests, three alternative methods for testing for equal treatment effects and equal carryover effects are proposed. A simulation study is conducted to …
Two-Factor Agricultural Experiment With Repeated Measures On One Factor In A Complete Randomized Design, Armando Garsd, María Del C. Fabrizio, María V. López
Two-Factor Agricultural Experiment With Repeated Measures On One Factor In A Complete Randomized Design, Armando Garsd, María Del C. Fabrizio, María V. López
Conference on Applied Statistics in Agriculture
A typical agricultural experiment involves comparisons of several treatments at different points in time. The ensuing lack of independence between observations of the same experimental unit may then impair the attainment of statistical significance by the standard analysis of variance, and calls for the application of more powerful methods. This paper addresses one such method, the so-called two-factor experiment with repeated measures on one factor. We discuss the adequacy of this model in the context of three concrete examples drawn from agricultural experimentation.
Analysis Of Repeated Measures Data, Ramon C. Littell
Analysis Of Repeated Measures Data, Ramon C. Littell
Conference on Applied Statistics in Agriculture
Data with repeated measures occur frequently in agricultural research. This paper is a brief overview of statistical methods for repeated measures data. Statistical analysis of repeated measures data requires special attention due to the correlation structure, which may render standard analysis of variance techniques invalid. For balanced data, multivariate analysis of variance methods can be employed and adjustments can be applied to univariate methods, as means of accounting for the correlation structure. But these analysis of variance methods do not apply readily with unbalanced data, and they overlook the regression on time. Regression curves for treatment groups can be obtained …
Analysis Of A Two Lactation Target Animal Safety Study Of Somidobove Sustained Release Injection In Multiparous Dairy Cows, L. V. Tonkinson, R. P. Basson, R. K. Mcguffey, A. Deldar, L. Fisher
Analysis Of A Two Lactation Target Animal Safety Study Of Somidobove Sustained Release Injection In Multiparous Dairy Cows, L. V. Tonkinson, R. P. Basson, R. K. Mcguffey, A. Deldar, L. Fisher
Conference on Applied Statistics in Agriculture
An overview is given of the primary basis for the scientific inference that somidobove sustained release injection is safe for multiparous dairy cows. The process of analysis and interpretation of the voluminous data collected from a target animal safety study which started with 28 cows and lasted two lactations is described. This was a repeated measures study with most of 60 variables being measured or summarized every 28 days resulting in approximately 1500 measurements per cow. The statistical analysis was designed to screen the variables for biological change caused by treatment and consisted of a univariate analysis of variance for …