Hao Chen

Hao Chen
University of British Columbia - Vancouver | UBC ·  Department of Statistics

Doctor of Philosophy
PhD in Statistics. Staff Data Scientist at NielsenIQ

About

17
Publications
1,167
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53
Citations

Publications

Publications (17)
Chapter
This research investigates if consumers were less price sensitive to life necessities during the COVID-19 pandemic via a demand modeling system. Consumers’ price sensitivity was explicitly quantified by the price elasticity of demand. Consumer behavior in nine categories of products considered as life necessities were studied in two non-overlapping...
Article
Linear Mixed Effects (LME) models have been widely applied in clustered data analysis in many areas including marketing research, clinical trials, and biomedical studies. Inference can be conducted using maximum likelihood approach if assuming Normal distributions on the random effects. However, in many applications of economy, business and medicin...
Conference Paper
Full-text available
This research investigates if consumers were less price sensitive to life necessities during the COVID-19 pandemic via a demand mod-eling system. Consumers' price sensitivity was explicitly quantified by the price elasticity of demand. Consumer behavior in nine categories of products considered as life necessities were studied in two non-overlappin...
Article
Full-text available
Tuition fees of full-time MBA programs with similar structure can vary greatly from around USD $20,000 to USD $220,000. This paper explores the effects of post-graduation salary, reputation, and their interaction on such high discrepancy in MBA tuition. Using a unique dataset of international MBA programs, we found that program value is positively...
Preprint
Full-text available
Linear Mixed Effects (LME) models have been widely applied in clustered data analysis in many areas including marketing research, clinical trials, and biomedical studies. Inference can be conducted using maximum likelihood approach if assuming Normal distributions on the random effects. However, in many applications of economy, business and medicin...
Article
Marketing mix models (MMMs) are statistical models for measuring the effectiveness of various marketing activities such as promotion, media advertisement, etc. In this research, we propose a comprehensive marketing mix model that captures the hierarchical structure and the carryover, shape and scale effects of certain marketing activities, as well...
Preprint
Full-text available
Linear Mixed Effects (LME) models have been widely applied in clustered data analysis in many areas including marketing research, clinical trials, and biomedical studies. Inference can be conducted using maximum likelihood approach if assuming Normal distributions on the random effects. However, in many applications of economy, business and medicin...
Preprint
Full-text available
Marketing mix models (MMMs) are statistical models for measuring the effectiveness of various marketing activities such as promotion, media advertisement, etc. In this research, we propose a comprehensive marketing mix model that captures the hierarchical structure and the carryover, shape and scale effects of certain marketing activities, as well...
Preprint
Full-text available
It is proved that the sum of n independent but non-identically distributed doubly truncated Normal distributions converges in distribution to a Normal distribution. It is also shown how the result can be applied in estimating a constrained mixed effects model.
Article
Latent class model (LCM), which is a finite mixture of different categorical distributions, is one of the most widely used models in statistics and machine learning fields. Because of its noncontinuous nature and flexibility in shape, researchers in areas such as marketing and social sciences also frequently use LCM to gain insights from their data...
Preprint
Full-text available
A computer code can simulate a system's propagation of variation from random inputs to output measures of quality. Our aim here is to estimate a critical output tail probability or quantile without a large Monte Carlo experiment. Instead, we build a statistical surrogate for the input-output relationship with a modest number of evaluations and then...
Article
Objective: To determine if patterns of hypoxic-ischemic brain injury on magnetic resonance imaging (MRI) in term newborns predict subsequent childhood epilepsy. Methods: This retrospective cohort study includes term newborns with encephalopathy (n = 181) born between 2004-2012 and admitted to British Columbia Children's Hospital. MRI was perform...
Preprint
Latent class model (LCM), which is a finite mixture of different categorical distributions, is one of the most widely used models in statistics and machine learning fields. Because of its non-continuous nature and the flexibility in shape, researchers in practice areas such as marketing and social sciences also frequently use LCM to gain insights f...
Article
Gaussian processes are widely used in the analysis of data from a computer model. Ideally, the analysis will yield accurate predictions with correct coverage probabilities of credible intervals. In this paper, we first review several existing Bayesian implementations in the literature. We show that Bayesian approaches with squared-exponential corre...
Article
Full-text available
Statistical methods based on a regression model plus a zero-mean Gaussian process (GP) have been widely used for predicting the output of a deterministic computer code. There are many suggestions in the literature for how to choose the regression component and how to model the correlation structure of the GP. This article argues that comprehensive,...

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