by Audrey Schnell

Odds Ratios and Relative Risks are often confused despite being unique concepts.  Why?

Well, both measure association between a binary outcome variable and a continuous or binary predictor variable. [click to continue…]


Pros and Cons of Treating Ordinal Variables as Nominal or Continuous

There are not a lot of statistical methods designed just for ordinal variables. But that doesn’t mean that you’re stuck with few options. There are more than you’d think…

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July 2016 Topic Webinar: Working with Truncated and Censored Data

This webinar will discuss what truncated and censored data is and how to identify it…

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June 2016 Topic Webinar: Zero Inflated Models

This webinar will explore two ways of modeling zero-inflated data: the Zero Inflated model and the Hurdle model. Both assume there are two different processes: one that affects the probability of a zero and one that affects the actual values, and both allow different sets of predictors for each process.

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Incorporating Graphs in Regression Diagnostics with Stata

In our upcoming Linear Models in Stata workshop, we will explore ways to find observations that influence the model. This is done in Stata via post-estimation commands. As the name implies, all post-estimation commands are run after running the model (regression, logit, mixed, etc)…

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Free May Craft of Statistical Analysis Webinar: Unlocking the Power of Stata’s Macros and Loops

There are many steps to analyzing a dataset. One of the first steps is to create tables and graphs of your variables in order to understand what is behind the thousands of numbers on your screen. But the type of table and graph you create depends upon the type of variable you are looking at…

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Linear Regression in Stata: Missing Data and the Stories it Might Tell

In a previous blog post we examined how to use the same sample when comparing the differences among regression models. Using different samples in our models could lead to erroneous conclusions when interpreting our models. But excluding observations can also result in inaccurate results…

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Issues with Truncated Data

Can we ignore the fact that a variable is bounded and just run our analysis as if the data wasn’t bounded?

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May 2016 Topic Webinar: Communicating Statistical Results: When to use tables vs graphs to tell the data’s story

In this webinar, we will discuss when tables and graphs are (and are not) appropriate and how people tend to engage with each of these media…

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April 2016 Topic Webinar: An Introduction to Kaplan-Meier Curves

In this talk, you will see a simple example of this using fruit fly data, and learn how to interpret the Kaplan-Meier curve to estimate survival probabilities and survival percentiles..

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