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The San Diego Chapter of the American Statistical Association

 seeks to sponsor educational, professional, and scientific

 activities that benefit professional statisticians, students

of statistics, and the San Diego Community at large. 


The next event is the 2016 Annual Business Meeting, April 27, 2016 (Wed).

Speaker: Dr. Mingan Yang, Asst Prof, Div of Epi & Biostatistics, SDSU

Date: April 27, 2016 (Wednesday)

Time: 5:30 to 8:00PM

5:30-6:00pm: Dinner

6:00-7:00pm: Dr. Yang’s presentation

7:00-7:30pm: Discussion

7:30–8:00pm: Business Meeting

 Location: Building CB2/1110, Pfizer La Jolla Campus,

                 10770 Science Center Drive, San Diego, CA 92121

 The meeting, including dinner, are free to all San Diego Chapter members!

$0: SDASA members, $5.00 student/retiree non-members, $10 other non-members.

Signup and pay at


Included in this year’s Business Meeting:

  • Dinner
  • Chapter news updates
  • Keynote presentation by Dr. Mingan Yang

In a linear mixed effects model, it is common practice to assume that the random effects follow a parametric distribution, such as a normal distribution with mean zero. However, in the case of variable selection, substantial violation of the normality assumption can potentially impact the subset selection and result in poor interpretation and even incorrect results. In nonparametric random effect models, the random effects generally have a non-zero mean, which causes an identifiability problem for the fixed effects that are paired with the random effects. In this article, we focus on a Bayesian method for variable selection. We characterize the subject specific random effects nonparametrically with a Dirichlet process and resolve the bias simultaneously. In particular, we propose flexible modeling of the conditional distribution of the random effects with changes across the predictor space. The approach is implemented using a stochastic search Gibbs sampler to identify subsets of fixed effects and random effects to be included in the model. Simulations are provided to evaluate and compare the performance of our approach to the existing ones. We then apply the new approach to a real data example, cross-country and inter-laboratory rodent uterotrophic bioassay.





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No matter how much reverence is paid to anything purporting to be "statistics," the term has no meaning unless the source, relevance, and truth are all checked.

 Tom Burman, The Dictionary of Misinformation, Statistics, use, misuses, and abuse of (p. 244.)






2015 Joint Statistical Meetings

August 8-13, 2015
Washington State Convention Center
800 Convention Place, Seattle, WA  98101



2016 Joint Statistical Meetings

July 30-August 4, 2016

McCormick Place, Chicago, IL



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There are a few statistical bloggers around the world who are listed below (in alphabetical order.)  If you know of any others, please let Patricia English know and she will update the links here.

John Johnson from Registrat-Mapi posts include statistics, clinical trials, and the scientific process. 

Yossi Levy blogs about statistics in Hebrew. 

Sanjay Matange of SAS blogs on data visualization with a focus on SAS ODS.

Naomi Robbins, graphic displays expert, blogs on effective graphics.       

David Smith of Revolution R posts daily on topics of interest to R users, including R and statistics. 

Rick Wicklin of SAS posts about SAS including code. 

The  site is a compilation of statistics blogs; some of the above bloggers are included on this site but there are many others.




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