Create your own conference schedule! Click here for full instructions

Abstract Detail



Conference Wide

Manage Goodale, Uromi [1].

Analysis of Ecological Communities using Structural Equation Modelling.

Structural equation modeling (SEM) is a general statistical modeling technique that can be used to explore the relationships among observed variables. Although many applications are in social and behavioral sciences, it is now more commonly used in biology, particularly in the assessment of ecological communities. Using SEM we can test theories or hypotheses that can be represented by a path diagram in which observed variables are usually depicted by boxes and hypothetical constructs measured by multiple indicators, referred to as latent variables, are represented by circles. In the path diagram the hypothesized effects among observed and latent variables are represented by arrows. If you are working with a complex study system with multifarious interrelations among your study variables in your data, this short course introducing the use of SEM is for you. In the first half of the one-day workshop we will introduce the theory and application of SEM using published research studies and data. In the second half of the workshop, we will discuss on the role of centering data, and provide hands on experience on how to handle missing data, non-normal data, categorical data, longitudinal data, etc. using the data that will be brought by the participants themselves or using example data sets from our own research work. If participants would like to use their own data for analyses, participants are requested to provide their own data two weeks in advance of the workshop date along with a variable explanation and a 500-word abstract describing the data and what the research questions that are being asked are. Hands-on sessions are included in order to ensure that all participants are able to perform the analyses using SEM software. Participants are also required to bring their own computer preloaded with the data analysis packages and R open source software program required for data analysis. This course will use several open-source R packages for data analysis as well as the generation of results figures. Therefore, a basic knowledge of R is necessary to get the most benefits from the full day workshop.


Log in to add this item to your schedule

1 - Guangxi University, Plant Ecophysiology And Evolution Group, State Key Laboratory Of Conservation And Utilization Of Subtropical Agro-bioresources, College Of Forestry,, Daxuedonglu 100, Nanning, 530005, China

Keywords:
none specified

Presentation Type: Workshop
Session: TBA
Location: /
Date: Thursday, January 1st, 1970
Time: TBA
Number:
Abstract ID:16
Candidate for Awards:None


Copyright © 2000-2020, Botanical Society of America. All rights reserved