activity
20162023
most citedMissing Data in Discrete Time State-Space Modeling of Ecological Momentary Assessment Data: A Monte-Carlo Study of Imputation Methods

6 citations · 13 across the 7 of their papers we have counts for

collaborators

7 papers

stat.ME2023★ 3 cited

Ordinal Outcome State-Space Models for Intensive Longitudinal Data

Teague R. Henry, Lindley R. Slipetz, Ami Falk +2

Intensive longitudinal (IL) data are increasingly prevalent in psychological science, coinciding with technological advancements that make it simple to deploy study designs such as…

stat.AP2023★ 1 cited

Analyzing Ecological Momentary Assessment Data with State-Space Models: Considerations and Recommendations

Lindley R. Slipetz, Jeremy W. Eberle, Cheri A. Levinson +3

Ecological momentary assessment (EMA) data have a broad base of application in the study of time trends and relations. In EMA studies, there are a number of design considerations w…

stat.ME2023★ 6 cited

Missing Data in Discrete Time State-Space Modeling of Ecological Momentary Assessment Data: A Monte-Carlo Study of Imputation Methods

Lindley R. Slipetz, Ami Falk, Teague R. Henry

When using ecological momentary assessment data (EMA), missing data is pervasive as participant attrition is a common issue. Thus, any EMA study must have a missing data plan. In t…

cs.SI2021

A purely data-driven framework for prediction, optimization, and control of networked processes: application to networked SIS epidemic model

Ali Tavasoli, Teague Henry, Heman Shakeri

Networks are landmarks of many complex phenomena where interweaving interactions between different agents transform simple local rule-sets into nonlinear emergent behaviors. While…

stat.ME2018★ 1 cited

Optimal Instrument Selection using Bayesian Model Averaging for Model Implied Instrumental Variable Two Stage Least Squares Estimators

Teague R. Henry, Zachary F. Fisher, Kenneth A. Bollen

Model-Implied Instrumental Variable Two-Stage Least Squares (MIIV-2SLS) is a limited information, equation-by-equation, non-iterative estimator for latent variable models. Associat…

cs.SI2016

Modeling community structure and topics in dynamic text networks

Teague Henry, David Banks, Christine Chai +1

The last decade has seen great progress in both dynamic network modeling and topic modeling. This paper draws upon both areas to create a Bayesian method that allows topic discover…

stat.ME2016★ 2 cited

Modeling Heterogeneous Peer Assortment Effects using Finite Mixture Exponential Random Graph Models

Teague R Henry, Kathleen M Gates, Mitchell J Prinstein +1

This article develops a class of models called Sender/Receiver Finite Mixture Exponential Random Graph Models (SRFM-ERGMs) that enables inference on networks. This class of models…