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SPSP provides online professional development to members at all career stages. Some of these opportunities are offered live and made available in recorded format, while others are only in video format.


Check back soon for upcoming Online Training opportunities.


“Creating Reproducible Research Reports Using R Markdown”

Michael Frank headshot

Stanford University

December 5, 2018
Format: Online Webinar

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Description:
R Markdown is a simple but very powerful way to mix R data analysis code and text. R Markdown documents are a great way to document your data analysis and create reproducible reports (e.g., that automatically render your graphs and tables and even your results section from your data). You can even use R Markdown to write your entire paper, avoiding copy-and-pasting your analyses, which can be a major source of errors in papers. The rendered documents look spiffy on the web and in print. In this workshop, we introduce R Markdown and show how it can be used as part of a reproducible writing workflow.

   

 

“A Practical Guide to Multilevel Modeling: Part 2”

Amie Gordon headshot

Amie M. Gordon (email)
University of California San Francisco

September 27, 2018
Time: 2:00-3:30PM ET
Format: Online Webinar

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Description:
This is the second of a two-part multilevel modeling (MLM) webinar for newbies as well as researchers who have been exposed to it through a prior class or workshop but still have lots of questions. Topics in Part 2 include: 

1. Fixed versus random effects – the difference between fixed and random effects and what changes in the analysis process when random slopes are allowed in the model.

2. Grand-mean versus group centering – what they are and when to use them, unconfounding within and between person effects.

3. Covariance matrices – cover the basics of the residual and random effects covariance matrices.

 

“A Practical Guide to Multilevel Modeling: Part 1”

Amie Gordon headshot

Amie M. Gordon (email)
University of California San Francisco

September 26, 2018
Time: 3:30-5:00PM ET

Format: Online Webinar

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Description:
This is the first of a two-part multilevel modeling (MLM) webinar for newbies as well as researchers who have been exposed to it through a prior class or workshop but still have lots of questions. Topics in Part 1 include: 

1. Identifying if MLM is necessary – the first step in MLM is figuring out whether data actually violates assumptions of independence.

2. Figuring out the nested structure of your data (including cross-classified models) – Identifying the sources of non-independence in your data, including the possibility of cross-classification.

3. Approaches to dealing with non-independence – when to deal with non-independence through random versus fixed factors.

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