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 […]
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 […]
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 […]
Panel data, also known as longitudinal data, consists of multiple observations of the same subject over time. Many disciplines will analyze such data using a random intercept or random coefficients model. In this workshop, another way of modeling such data will be discussed: using fixed effects. Fixed effects methods can be used in longitudinal studies […]
Missing data are very common in all types of data sets, but most statistical procedures assume that all data are observed. The result is that most standard statistical software packages automatically drop from the analysis all observations with any missing data. This approach can lead to very low sample sizes and biased results. This two-part […]
Time series analysis concerns with methods for visualization and statistical analysis of data collected sequentially over time. This workshop is designed to introduce researchers to basics of time series data exploration and modeling. After attending the workshop, you should be able to use standard R packages to: perform exploratory data analysis with time series;- correct […]