In this video I will answer a question from a recent webinar Random Intercept and Random Slope Models.
We are answering questions here because we had over 500 people live on the webinar so we didn’t have time to get through all the questions.
If you missed the webinar live, this and the other questions in this series may make more sense if you watch that first. It was part of our free webinar series, The Craft of Statistical Analysis, and you can sign up to get the free recording, handout, and data set below:
In this video I will answer a question from a recent webinar Random Intercept and Random Slope Models.
We are answering questions here because we had over 500 people live on the webinar so we didn’t have time to get through all the questions.
If you missed the webinar live, this and the other questions in this video series may make more sense if you watch that first. It was part of our free webinar series, The Craft of Statistical Analysis, and you can sign up to get the free recording, handout, and data set at this link:
In this video I will answer a question from a recent webinar Random Intercept and Random Slope Models.
We are answering questions here because we had over 500 people live on the webinar so we didn’t have time to get through all the questions.
If you missed the webinar live, this and the other questions in this series may make more sense if you watch that first. It was part of our free webinar series, The Craft of Statistical Analysis, and you can sign up to get the free recording, handout, and data set at this link:
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.
There certainly isn’t much point in running a frequency table for a continuous variable with hundreds of unique observations. Creating a boxplot to look for outliers doesn’t make much sense if the variable is categorical. Creating a histogram for a dummy variable would be senseless as well.
How should you start this process? Should you create a spreadsheet listing all the names of the variables and list what type of variable they are? Should you paste the names into a Word document?
In this free webinar with Stata expert Jeff Meyer, you will discover the code to quickly determine the type of every variable in a dataset. By simply pressing the execute button on a do-file you will observe Stata placing each variable in a group (the macro) based on the type of variable it is.
You will watch, through the use of loops, Stata create the proper table and graph for each type of variable in a matter of minutes and output the data into a pdf file for future viewing. You will also receive the code to recreate and practice what you’ve learned.
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Title: Improving Your Productivity by Unlocking the Power of Stata’s Macros and Loops Date: Thurs, May 26, 2016 Time: 1-2 pm EDT Presenter: Jeff Meyer
This webinar has already taken place. Please sign up below to get access to the video recording.
Statistically Speaking members can access this recording from the Analysis Toolbox Resources page at the Programs Center without signing up.
Jeff Meyer is a statistical consultant with The Analysis Factor, a stats mentor for Statistically Speaking membership, and a workshop instructor. Read more about Jeff here.
Stata has perhaps the best support resources of any statistical software
to help you prepare and analyze your data. These resources are helpful
for all skill levels, from beginners to advanced users.
For just about any Stata command, there are FAQs, text books, Stata
Journal articles, and third party add-ons, not to mention the built in
help page.
Even these help pages are detailed — broken into subsections;
description, syntax, menu, and examples.
Learning the nuances of the resources and how to quickly find the one
you need will help you create accurate analysis in significantly less time.
We will start by exploring commands with few options such as *generate*
and *navigate* to commands with many options such as *egen.*
**
This free one hour webinar will be packed full of information that will
help reduce those frustrating moments that we all experience when using
software.
Title: How to Benefit from Stata’s Bountiful Help Resources Date: Thurs Dec 17, 2015 Time: 2:00pm EST Presenter: Jeff Meyer
This webinar has already taken place. Please sign up below to get access to the video recording.
Statistically Speaking members can access this recording from the Analysis Toolbox Resources page at the Programs Center without signing up.
Share the free December 2015 webinar with others!
Jeff Meyer is a statistical consultant with The Analysis Factor, a stats mentor for Statistically Speaking membership, and a workshop instructor. Read more about Jeff here.
This free, one-hour webinar is part of our regular Craft of Statistical Analysis series. In it, we will introduce and demonstrate two of the core concepts of mixed modeling—the random intercept and the random slope.
Most scientific fields now recognize the extraordinary usefulness of mixed models, but they’re a tough nut to crack for someone who didn’t receive training in their methodology.
But it turns out that mixed models are actually an extension of linear models. If you have a good foundation in linear models, the extension to mixed models is more of a step than a leap. (Okay, a large step, but still).
You’ll learn what random intercepts and slopes mean, what they do, and how to decide if one or both are needed. It’s the first step in understanding mixed modeling.
Date: Friday, August 21, 2015 Time: 12pm EDT (New York time) Cost: Free
***Note: This webinar has already taken place. Sign up below to get access to the video recording of the webinar.
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