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        Quantitative Psychology and Statistics Lab


 
                                
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Welcome to the Quantitative Psychology and Statistics Lab!



As data can be produced and stored more massively and cheaply from various sources, we have entered the era of Big Data.  To the extent that data can be analyzed, we may be able to gain a completely new perspective on our world, on how people interact, spend their resources, and organize their time. Though promises are held, the high-dimensionality and huge size of data sets can lead to inferential problems of their own—particularly spurious correlations, noise accumulation, and incidental homogeneity. Many traditional methods that perform well for moderate sample size or low dimensional data do not scale to massive data or high dimensional data. Therefore,
new statistical thinking and computational approaches are required to handle these challenges.
 
Our lab focuses on the development and application of advanced statistical models to analyze complex and high dimensional data (e.g. neuroimaging data, complex behavioral data). In particular, we have been focused on using multimodal neuroimaging (e.g., MRI, DTI, fMRI, PET) to examine neurodegenerative diseases (e.g., Alzheimer’s disease) and psychiatric disorders (e.g., PTSD, eating disorders).  The modeling approach we take includes machine learning, Bayesian inference, and high dimensional data analysis. In addition, our group works on the statistical methods development for informing real time individualized sequences of treatments (Just-in-Time Adaptive Interventions) and integrating multimodal data generated from wearable devices (e.g., fitness trackers, heart rate monitors) in the context of weight loss maintenance and eating disorders. 

Please visit our research page for more information about our work.




Prospective Students

Our lab has funded phd student position available. Prospective students who are interested in joining our research group should contact Zoe Zhang (fengqing.zhang@drexel.edu).