29 citations · 32 across the 6 of their papers we have counts for
6 papers
Stochastic Search Variable Selection for Bayesian Generalized Linear Mixed Effect Models
Feng Ding, Ian Laga
Variable selection remains a difficult problem, especially for generalized linear mixed models (GLMMs). While some frequentist approaches to simultaneously select joint fixed and r…
Estimating and Correcting Degree Ratio Bias in the Network Scale-up Method
Ian Laga, Jessica P. Kunke, Tyler H. McCormick +1
The Network Scale-up Method (NSUM) uses social networks and answers to "How many X's do you know?" questions to estimate sizes of groups excluded by standard surveys. This paper ad…
Comparing the Robustness of Simple Network Scale-Up Method (NSUM) Estimators
Jessica P. Kunke, Ian Laga, Xiaoyue Niu +1
The network scale-up method (NSUM) is a cost-effective approach to estimating the size or prevalence of a group of people that is hard to reach through a standard survey. The basic…
A Correlated Network Scale-up Model: Finding the Connection Between Subpopulations
Ian Laga, Le Bao, Xiaoyue Niu
Aggregated relational data (ARD), formed from "How many X's do you know?" questions, is a powerful tool for learning important network characteristics with incomplete network data.…
Thirty Years of The Network Scale up Method
Ian Laga, Le Bao, Xiaoyue Niu
Estimating the size of hard-to-reach populations is an important problem for many fields. The Network Scale-up Method (NSUM) is a relatively new approach to estimate the size of th…
Modeling the Marked Presence-only Data: A Case Study of Estimating the Female Sex Worker Size in Malawi
Ian Laga, Xiaoyue Niu, Le Bao
Certain subpopulations like female sex workers (FSW), men who have sex with men (MSM), and people who inject drugs (PWID) often have higher prevalence of HIV/AIDS and are difficult…