The JMP DOE platform provides a user friendly way to construct study designs that accommodate a variety of types of factors and constraints common to experimental research. This workshop will illustrate how to use this platform to design, evaluate and compare: Full factorial designs Randomized block designs Incomplete block designs Split plot designs Response surface […]
One of the first steps in planning a new study is determining an appropriate sample size. A sample size should be large enough to have a high probability of detecting an effect of a treatment but small enough that it is within the confines of the study?s budget and minimizes the potential risks to human […]
Determining appropriate sample sizes for experiments can be a challenge, especially when the anticipated statistical analysis includes mixed models. In this hands-on workshop, we will discuss the goals of sample size and power calculations and how they can be used, as well as ways to simulate sample sizes in R. This method allows for understanding […]
This workshop will provide an introduction to statistical methods and software for differential expression analysis based on RNA-seq read counts. All of the methods considered involve a negative binomial distribution for the counts as a starting point. In addition, the statistical methods all utilize some form of empirical Bayes analysis by which gene-specific error variances are ‘shrunk’ towards […]
This workshop is intended for people who have taken an introductory statistic course and feel comfortable with the material covered in our Introductory Statistics Using Stata workshop. This is a hands-on workshop and all methods will be demonstrated using the statistical software package Stata. Topics that will be covered include: Chi-squared tests One-way and two-way […]
Multilevel models (also referred to as hierarchical models or mixed models) are a class of statistical models that can be used when observations are not independent. Non-independence can occur when data is clustered due to the study design (e.g., data collected on households and their individual members or blocked agricultural studies) or when data is […]
A pretest-posttest research design is a simple form of a repeated-measures design where a baseline measurement is taken on subjects randomized to control and intervention groups followed by a post-intervention measurement on the same groups. Generally, the analysis is based on testing three hypotheses concerning (1) the difference in pretest measurements between the control and […]
In a longitudinal study data has been collected on the same observation over time. Since the repeated measures taken on the same observations are not independent from each other this is a type of multilevel data and special care needs to be taken during the analysis to account for this non-independence. These types of data […]
This workshop is intended for people who feel comfortable with the material covered in our Introductory Statistics Using Stata workshop. We will use hands-on examples to cover: Sub-setting by observations or by variables Creating new variables as functions of existing variables Aggregation/summarizing by observations or by variables Reshaping (pivoting) from wide to tall or from […]
This workshop is intended for people who feel comfortable with the material covered in our Introductory Statistics Using R workshop. The ggplot2 package is a versatile tool for data visualization in the free statistical software package R. ggplot2 uses the “grammar of graphics” to build plots by adding the individual components of a plot layer […]