208 related articles for article (PubMed ID: 23795233)
1. A Model-Based fMRI Analysis with Hierarchical Bayesian Parameter Estimation.
Ahn WY; Krawitz A; Kim W; Busmeyer JR; Brown JW
J Neurosci Psychol Econ; 2011 May; 4(2):95-110. PubMed ID: 23795233
[TBL] [Abstract][Full Text] [Related]
2. HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python.
Wiecki TV; Sofer I; Frank MJ
Front Neuroinform; 2013; 7():14. PubMed ID: 23935581
[TBL] [Abstract][Full Text] [Related]
3. Predicting individual brain functional connectivity using a Bayesian hierarchical model.
Dai T; Guo Y;
Neuroimage; 2017 Feb; 147():772-787. PubMed ID: 27915121
[TBL] [Abstract][Full Text] [Related]
4. Using Bayesian hierarchical parameter estimation to assess the generalizability of cognitive models of choice.
Scheibehenne B; Pachur T
Psychon Bull Rev; 2015 Apr; 22(2):391-407. PubMed ID: 25134469
[TBL] [Abstract][Full Text] [Related]
5. Classical and Bayesian inference in neuroimaging: applications.
Friston KJ; Glaser DE; Henson RN; Kiebel S; Phillips C; Ashburner J
Neuroimage; 2002 Jun; 16(2):484-512. PubMed ID: 12030833
[TBL] [Abstract][Full Text] [Related]
6. Dynamic models of choice.
Heathcote A; Lin YS; Reynolds A; Strickland L; Gretton M; Matzke D
Behav Res Methods; 2019 Apr; 51(2):961-985. PubMed ID: 29959755
[TBL] [Abstract][Full Text] [Related]
7. Comparative Analysis of Behavioral Models for Adaptive Learning in Changing Environments.
Marković D; Kiebel SJ
Front Comput Neurosci; 2016; 10():33. PubMed ID: 27148030
[TBL] [Abstract][Full Text] [Related]
8. Does the reliability of computational models truly improve with hierarchical modeling? Some recommendations and considerations for the assessment of model parameter reliability : Reliability of computational model parameters.
Katahira K; Oba T; Toyama A
Psychon Bull Rev; 2024 May; ():. PubMed ID: 38717680
[TBL] [Abstract][Full Text] [Related]
9. Likelihood-based parameter estimation and comparison of dynamical cognitive models.
Schütt HH; Rothkegel LOM; Trukenbrod HA; Reich S; Wichmann FA; Engbert R
Psychol Rev; 2017 Jul; 124(4):505-524. PubMed ID: 28447811
[TBL] [Abstract][Full Text] [Related]
10. A Hierarchical Bayesian Implementation of the Experience-Weighted Attraction Model.
Zhang Z; Chandra S; Kayser A; Hsu M; Warren JL
Comput Psychiatr; 2020 Nov; 4():40-60. PubMed ID: 33426270
[TBL] [Abstract][Full Text] [Related]
11. Sensitivity analysis and estimation using a hierarchical Bayesian method for the parameters of the FvCB biochemical photosynthetic model.
Han T; Zhu G; Ma J; Wang S; Zhang K; Liu X; Ma T; Shang S; Huang C
Photosynth Res; 2020 Jan; 143(1):45-66. PubMed ID: 31659624
[TBL] [Abstract][Full Text] [Related]
12. Simultaneous Hierarchical Bayesian Parameter Estimation for Reinforcement Learning and Drift Diffusion Models: a Tutorial and Links to Neural Data.
Pedersen ML; Frank MJ
Comput Brain Behav; 2020 Dec; 3(4):458-471. PubMed ID: 35128308
[TBL] [Abstract][Full Text] [Related]
13. Decision Making Profile of Positive and Negative Anticipatory Skin Conductance Responders in an Unlimited-Time Version of the IGT.
Merchán-Clavellino A; Salguero-Alcañiz MP; Barbosa F; Alameda-Bailén JR
Front Psychol; 2019; 10():2237. PubMed ID: 31681074
[TBL] [Abstract][Full Text] [Related]
14. Part 2. Development of Enhanced Statistical Methods for Assessing Health Effects Associated with an Unknown Number of Major Sources of Multiple Air Pollutants.
Park ES; Symanski E; Han D; Spiegelman C
Res Rep Health Eff Inst; 2015 Jun; (183 Pt 1-2):51-113. PubMed ID: 26333239
[TBL] [Abstract][Full Text] [Related]
15. A hierarchical model for probabilistic independent component analysis of multi-subject fMRI studies.
Guo Y; Tang L
Biometrics; 2013 Dec; 69(4):970-81. PubMed ID: 24033125
[TBL] [Abstract][Full Text] [Related]
16. Hierarchical Bayesian inference for concurrent model fitting and comparison for group studies.
Piray P; Dezfouli A; Heskes T; Frank MJ; Daw ND
PLoS Comput Biol; 2019 Jun; 15(6):e1007043. PubMed ID: 31211783
[TBL] [Abstract][Full Text] [Related]
17. Variational Bayesian Parameter Estimation Techniques for the General Linear Model.
Starke L; Ostwald D
Front Neurosci; 2017; 11():504. PubMed ID: 28966572
[TBL] [Abstract][Full Text] [Related]
18. Hierarchical Bayesian estimation and hypothesis testing for delay discounting tasks.
Vincent BT
Behav Res Methods; 2016 Dec; 48(4):1608-1620. PubMed ID: 26542975
[TBL] [Abstract][Full Text] [Related]
19. Collinear Latent Variables in Multilevel Confirmatory Factor Analysis: A Comparison of Maximum Likelihood and Bayesian Estimations.
Can S; van de Schoot R; Hox J
Educ Psychol Meas; 2015 Jun; 75(3):406-427. PubMed ID: 29795827
[TBL] [Abstract][Full Text] [Related]
20.
; ; . PubMed ID:
[No Abstract] [Full Text] [Related]
[Next] [New Search]
