rtmpt: An R package for fitting response-time extended multinomial processing tree models

Benefits of response time-extended multinomial processing tree models: A reply to Starns (2018)

Psychonomic Bulletin & Review ◽

10.3758/s13423-019-01663-0 ◽

2020 ◽

Vol 27 (3) ◽

pp. 571-580 ◽

Cited By ~ 1

Author(s):

Daniel W. Heck ◽

Edgar Erdfelder

Keyword(s):

Response Time ◽

A context-free language for binary multinomial processing tree models

10.1016/j.jmp.2009.07.009 ◽

2009 ◽

Vol 53 (6) ◽

pp. 547-561 ◽

Cited By ~ 10

Author(s):

Brendan P. Purdy ◽

William H. Batchelder

Keyword(s):

Context Free Language ◽

Tree Models ◽

Context Free ◽

Free Language

Cognitive psychometrics: Assessing storage and retrieval deficits in special populations with multinomial processing tree models.

Psychological Assessment ◽

10.1037/1040-3590.14.2.184 ◽

2002 ◽

Vol 14 (2) ◽

pp. 184-201 ◽

Cited By ~ 53

Author(s):

David M. Riefer ◽

Bethany R. Knapp ◽

William H. Batchelder ◽

Donald Bamber ◽

Victor Manifold

Keyword(s):

Special Populations ◽

Storage And Retrieval ◽

Advances in clinical cognitive science: Formal modeling of processes and symptoms. ◽

Using Multinomial Processing Tree Models to Measure Cognitive Deficits in Clinical Populations.

10.1037/11556-001 ◽

2007 ◽

pp. 19-50 ◽

Cited By ~ 9

Author(s):

William H. Batchelder ◽

David M. Riefer

Keyword(s):

Cognitive Deficits ◽

Tree Models ◽

Clinical Populations

Cognitive psychometrics: Using multinomial processing tree models as measurement tools.

Measuring psychological constructs: Advances in model-based approaches. ◽

10.1037/12074-004 ◽

2010 ◽

pp. 71-93 ◽

Cited By ~ 8

Author(s):

William H. Batchelder

Keyword(s):

Measurement Tools ◽

An application of multinomial processing tree models and Bayesian methods to understanding memory impairment

10.1016/j.jmp.2020.102328 ◽

2020 ◽

Vol 95 ◽

pp. 102328

Author(s):

Michael D. Lee ◽

Jason R. Bock ◽

Isaiah Cushman ◽

William R. Shankle

Keyword(s):

Bayesian Methods ◽

Memory Impairment ◽

Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach

Psychometrika ◽

10.1007/s11336-009-9141-0 ◽

2009 ◽

Vol 75 (1) ◽

pp. 70-98 ◽

Cited By ~ 87

Author(s):

Karl Christoph Klauer

Keyword(s):

Latent Trait ◽

Pooling data versus averaging model fits for some prototypical multinomial processing tree models

10.1016/j.jmp.2009.06.005 ◽

2009 ◽

Vol 53 (6) ◽

pp. 562-576 ◽

Cited By ~ 18

Author(s):

Richard A. Chechile

Keyword(s):

Tree Models ◽

Model Fits

Representing parametric order constraints in multi-trial applications of multinomial processing tree models

10.1016/j.jmp.2004.03.002 ◽

2004 ◽

Vol 48 (4) ◽

pp. 215-229 ◽

Cited By ~ 29

Author(s):

Bethany R Knapp ◽

William H Batchelder

Keyword(s):

Order Constraints ◽

Multinomial processing tree models: An implementation

Behavior Research Methods Instruments &amp Computers ◽

10.3758/bf03200747 ◽

1999 ◽

Vol 31 (4) ◽

pp. 689-695 ◽

Cited By ~ 23

Author(s):

Xiangen Hu

Keyword(s):