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Timothy Hayes
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Estimating the reproducibility of psychological science
Open Science Collaboration
Science 349 (6251), aac4716, 2015
91832015
An open, large-scale, collaborative effort to estimate the reproducibility of psychological science
Open Science Collaboration
Perspectives on Psychological Science 7 (6), 657-660, 2012
7282012
Immersive virtual environments versus physical built environments: A benchmarking study for building design and user-built environment explorations
A Heydarian, JP Carneiro, D Gerber, B Becerik-Gerber, T Hayes, W Wood
Automation in Construction 54, 116-126, 2015
3472015
Social Influence on consumer decisions: Motives, modes, and consequences
W Wood, T Hayes
Journal of Consumer Psychology 22 (3), 324-328, 2012
1732012
Using Classification and Regression Trees (CART) and random forests to analyze attrition: Results from two simulations.
T Hayes, S Usami, R Jacobucci, JJ McArdle
Psychology and aging 30 (4), 911, 2015
1572015
Influence of LEED branding on building occupants' pro-environmental behavior
S Khashe, A Heydarian, D Gerber, B Becerik-Gerber, T Hayes, W Wood
Building and Environment 94, 477-488, 2015
772015
SAVES: A sustainable multiagent application to conserve building energy considering occupants
J Kwak, P Varakantham, R Maheswaran, M Tambe, F Jazizadeh, ...
Proceedings of the 11th International Conference on Autonomous Agents and ¡¦, 2012
732012
Inferring longitudinal relationships between variables: Model selection between the latent change score and autoregressive cross-lagged factor models
S Usami, T Hayes, JJ McArdle
Structural Equation Modeling: A Multidisciplinary Journal 23 (3), 331-342, 2016
672016
Immersive virtual environments: experiments on impacting design and human building interaction
A Heydarian, JP Carneiro, D Gerber, B Becerik-Gerber, T Hayes, W Wood
Rethinking Comprehensive Design: Speculative Counterculture, Proceedings of ¡¦, 2014
492014
On the mathematical relationship between latent change score and autoregressive cross-lagged factor approaches: Cautions for inferring causal relationship between variables
S Usami, T Hayes, JJ McArdle
Multivariate Behavioral Research 50 (6), 676-687, 2015
482015
Thermally stimulated current and high temperature resistivity measurements of 4H semi-insulating silicon carbide
KC Mandal, PG Muzykov, R Krishna, T Hayes, TS Sudarshan
Solid state communications 151 (7), 532-535, 2011
432011
A comparison of multilevel imputation schemes for random coefficient models: fully conditional specification and joint model imputation with random covariance matrices
CK Enders, T Hayes, H Du
Multivariate behavioral research 53 (5), 695-713, 2018
342018
Adolescent cannabis use and its associations with decision-making and episodic memory: Preliminary results from a longitudinal study.
JC Duperrouzel, SW Hawes, C Lopez-Quintero, I Pacheco-Colón, S Coxe, ...
Neuropsychology 33 (5), 701, 2019
322019
Factor score regression in the presence of correlated unique factors
T Hayes, S Usami
Educational and psychological measurement 80 (1), 5-40, 2020
312020
R-squared change in structural equation models with latent variables and missing data
T Hayes
Behavior Research Methods 53 (5), 2127-2157, 2021
252021
Factor score regression in connected measurement models containing cross-loadings
T Hayes, S Usami
Structural Equation Modeling: A Multidisciplinary Journal 27 (6), 942-951, 2020
202020
Juror perceptions of intoxicated suspects¡¯ interrogation-related behaviors
A Mindthoff, JR Evans, G Perez, SA Woestehoff, AP Olaguez, JZ Klemfuss, ...
Criminal Justice and Behavior 47 (2), 222-246, 2020
182020
A resilience framework: Sexual health trajectories of youth with maltreatment histories
NM Fava, LY Bay-Cheng, TH Nochajski, JC Bowker, T Hayes
Journal of Trauma & Dissociation 19 (4), 444-460, 2018
182018
Fitting structural equation model trees and latent growth curve mixture models in longitudinal designs: The influence of model misspecification
S Usami, T Hayes, J McArdle
Structural Equation Modeling: A Multidisciplinary Journal 24 (4), 585-598, 2017
182017
Should we impute or should we weight? Examining the performance of two CART-based techniques for addressing missing data in small sample research with nonnormal variables
T Hayes, JJ McArdle
Computational Statistics & Data Analysis 115, 35-52, 2017
162017
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