Information about past workshops is available here.
Power Analysis for ANOVA and Repeated Measures ANOVA
Power analysis is routinely used to determine if the sample size is sufficiently large to detect the treatment effects for a given significance level. This workshop will cover two commonly used designs: ANOVA and rANOVA. The fundamentals of power analysis will be presented. Several motivating
examples will be given. GPower will be introduced and illustrated during the workshop.
Date: Tuesday, April 10, 5:00PM – 6:00PM
Data Visualizations with R Shiny
Shiny is an R package that makes it easy to build interactive web apps from R. Shiny combines the computational power of R with the interactivity of the modern web. This workshop will introduce the basics of R Shiny, including the basic structure of a shiny app and how to make interactive visualizations.
Date: Wednesday, April 18, 12:00PM – 1:00PM
Missing Data in Surveys
Missing data are frequently encountered in surveys. This workshop will provide a brief overview of survey data and introduce types of missing data mechanisms. Several statistical methods in analyzing missing data will be discussed. Illustrative case studies will be presented in analyzing missing data using SPSS.
Date: Thursday, April 26, 4:00PM – 5:00PM
A 10-Year Progress Report from SCS (2008–2018) and a SCS Case Study
An in-depth and comprehensive report of the consulting services the SCS has provided during the last 10 years and A case study introducing the statistical methods, interactive tools, and data visualization the consulting team has developed/created for an ongoing consulting project with the University’s office for Utility Operations and Energy Management.
Date: Thursday, May 10, 2018, 9:15AM – 10:15AM
Methods and Tools for Exploratory Data Analysis with R
Exploratory data analysis (EDA) is a useful and effective approach to analyzing data to summarize their main characteristics, often with visualizations. The goal of EDA is to explore and understand the data, possibly formulating hypotheses that could lead to new data collection and experiments.
Date: Thursday, May 10, 2018, 10:30AM – 12:00PM
Analysis of Patient-Reported Outcomes
Patient-reported outcomes are often relevant in studying a variety of diseases and outcomes that cannot be assessed adequately without a patients evaluation and whose key questions require patients input on the impact of a disease or a treatment. To be useful to patients, researchers and decision makers, a patient-reported outcome (PRO) must undergo a validation process to support that it measures what it is intended to measure accurately and reliably. In this workshop, after presentation of some key elements on the development of a PRO measure, the core topics of validity and reliability of a PRO measure will be discussed. Exploratory and confirmatory factor analyses, techniques to understand the underlying structure of a PRO measure, will be described. The topic of mediation modeling will be presented as a way to identify and explain the mechanism that underlies
an observed relationship between an independent variable and a dependent variable via the inclusion of a third variable called the mediator variable. Also discussed will be item response theory and, time permitting, longitudinal analysis. Illustrations will be provided mainly through real-life and simulated examples.
Date: Thursday, May 10, 2018, 1:15PM – 2:45PM
Incorporating Statistics into Research Grants
This presentation will cover the statistical components of research grants typically required for successful applications. Topics will include a review of study types and their statistical characteristics, formulation of specific aims and hypotheses, development of a statistical plan for
your research grant, review of sample size and power and practical advice on how to justify your sample size. This will be a non-technical session geared towards research scientists who prepare grants and applied statisticians involved in collaborative studies.
Date: Thursday, May 10, 2018, 3:00PM – 4:30PM