APS Sponsoring Committees: Epidemiology; Crop Loss Assessment and Risk Evaluation (CARE)
Have you been avoiding attending one of the statistical workshops over the years because you felt that the topic was over your head? Do you feel you need to shake off that rust when it comes to statistics? If so, this is the statistical workshop for you! R (www.r-project.org) is a programming package for statistical computing and graphics and has become extremely popular, especially since it is free. In this workshop, we will introduce R and illustrate some of the tools that are available for using R, including graphical and statistical. The focus of this workshop will be at an introductory level and should be understandable to all who are interested in learning more about statistics and statistical computing. This workshop will follow the tradition of the Epidemiology Committee's workshops on “bringing statistical analysis to the masses.” All registrants will need to have a laptop with R installed. The workshop is limited to 60 participants.
APS Sponsoring Committee: Extension
This will be a hands-on workshop to develop skills for specific Internet tools used in the dissemination of information. The main focus will be on creating podcasts and using syndicated content. Participants will learn to make a short (30 seconds to 1 minute) podcast in this workshop and make use of syndication services to deliver it to a variety of audiences. The workshop will support both Mac and PC users.
It is now common to use linear mixed models (LMMs) instead of traditional ANOVA to analyze data from designed experiments. LMMs formally handle experiments with both fixed (e.g., fungicide treatment) and random (e.g., block, location) effects and properly estimate test statistics and standard errors for all the effects of interest under a wide range of circumstances. Although computationally more intensive than ANOVA, it is straightforward with LMMs to directly and correctly analyze data from experiments with two or more sources of variation (e.g., split plots); account for unequal variability (i.e., variances dependent on treatment) in determining the effect of experimental factors; properly test for the effects of repeated measures (such as time during the growing season); and account for the correlation of spatially-referenced data. Attendees will learn to use the MIXED and new GLIMMIX procedures of SAS to analyze data from common experimental designs in plant pathology. Material covered for the first time in the mixed-model workshop will introduce generalized linear mixed models (GLMMs) for analyzing discrete data; new graphical methods for assessing model fits; and high-performance mixed models for analyzing normal data when there are literally thousands of treatments or levels of the random effects. Multiple comparisons in the context of mixed models will also be discussed. This workshop will follow the tradition of the Epidemiology Committee’s workshops on “bringing statistical analysis to the masses.” All attendees must bring a laptop computer with version 9.2 of SAS installed. The workshop enrollment is limited to 60 participants; previous attendees can repeat the workshop.
APS Sponsoring Committees: Editorial Board, Publications Board
This workshop on publishing in APS journals will cover important aspects of preparing and submitting manuscripts to Plant Disease, Phytopathology and MPMI. The workshop will provide an overview of the review and publication process and provide guidelines for successful publishing. Participants will gain an understanding of the roles of editors-in-chief, senior editors, associate editors, and anonymous peer reviewers. Emphasis will be put on practical tips for scientific writing that will facilitate publication in APS journals. Topics such as proper formatting, authorship, plagiarism, reviewing, and appropriate subject matter for each journal will be addressed. The organizers and speakers are editors-in-chief with extensive experience in reviewing and publishing in APS journals. This workshop is geared towards graduate students and early career scientists.