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You searched for +publisher:"Georgia Tech" +contributor:("Spieler, Daniel H."). Showing records 1 – 5 of 5 total matches.

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Georgia Tech

1. McGlynn, Sean Andrew. Investigating proximal predictors of intraindividual affect variability in older adults.

Degree: MS, Psychology, 2016, Georgia Tech

 The aging process is often coupled with major life changes such as retirement, death of friends and family members, and declines in physical and psychological… (more)

Subjects/Keywords: Affect; Emotions; Emotional variability; Intraindividual variability; Emotion regulation; Multilevel modeling; Aging; Older adults; Stress; Pain; Subjective health; Life space; Technology

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APA (6th Edition):

McGlynn, S. A. (2016). Investigating proximal predictors of intraindividual affect variability in older adults. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55048

Chicago Manual of Style (16th Edition):

McGlynn, Sean Andrew. “Investigating proximal predictors of intraindividual affect variability in older adults.” 2016. Masters Thesis, Georgia Tech. Accessed December 11, 2019. http://hdl.handle.net/1853/55048.

MLA Handbook (7th Edition):

McGlynn, Sean Andrew. “Investigating proximal predictors of intraindividual affect variability in older adults.” 2016. Web. 11 Dec 2019.

Vancouver:

McGlynn SA. Investigating proximal predictors of intraindividual affect variability in older adults. [Internet] [Masters thesis]. Georgia Tech; 2016. [cited 2019 Dec 11]. Available from: http://hdl.handle.net/1853/55048.

Council of Science Editors:

McGlynn SA. Investigating proximal predictors of intraindividual affect variability in older adults. [Masters Thesis]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55048


Georgia Tech

2. King, David R. A bayesian solution for the law of categorical judgment with category boundary variability and examination of robustness to model violations.

Degree: MS, Psychology, 2013, Georgia Tech

 Previous solutions for the the Law of Categorical Judgment with category boundary variability have either constrained the standard deviations of the category boundaries in some… (more)

Subjects/Keywords: Scaling; Measurement; Thurstone; Bayesian estimation; MCMC; Simulation study; Law of categorical judgment; Method of successive intervals; Signal detection theory

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APA (6th Edition):

King, D. R. (2013). A bayesian solution for the law of categorical judgment with category boundary variability and examination of robustness to model violations. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52960

Chicago Manual of Style (16th Edition):

King, David R. “A bayesian solution for the law of categorical judgment with category boundary variability and examination of robustness to model violations.” 2013. Masters Thesis, Georgia Tech. Accessed December 11, 2019. http://hdl.handle.net/1853/52960.

MLA Handbook (7th Edition):

King, David R. “A bayesian solution for the law of categorical judgment with category boundary variability and examination of robustness to model violations.” 2013. Web. 11 Dec 2019.

Vancouver:

King DR. A bayesian solution for the law of categorical judgment with category boundary variability and examination of robustness to model violations. [Internet] [Masters thesis]. Georgia Tech; 2013. [cited 2019 Dec 11]. Available from: http://hdl.handle.net/1853/52960.

Council of Science Editors:

King DR. A bayesian solution for the law of categorical judgment with category boundary variability and examination of robustness to model violations. [Masters Thesis]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/52960


Georgia Tech

3. Martinez, David. Individual differences in signed word learning among hearing adults.

Degree: MS, Psychology, 2016, Georgia Tech

 The present study was conducted in order to identify predictors of signed word learning in hearing non-signers. 107 hearing non-signing adults participated, completing a sign-word… (more)

Subjects/Keywords: Word learning; Sign language acquisition; M2L2; Sign learning; Language aptitude

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APA (6th Edition):

Martinez, D. (2016). Individual differences in signed word learning among hearing adults. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59167

Chicago Manual of Style (16th Edition):

Martinez, David. “Individual differences in signed word learning among hearing adults.” 2016. Masters Thesis, Georgia Tech. Accessed December 11, 2019. http://hdl.handle.net/1853/59167.

MLA Handbook (7th Edition):

Martinez, David. “Individual differences in signed word learning among hearing adults.” 2016. Web. 11 Dec 2019.

Vancouver:

Martinez D. Individual differences in signed word learning among hearing adults. [Internet] [Masters thesis]. Georgia Tech; 2016. [cited 2019 Dec 11]. Available from: http://hdl.handle.net/1853/59167.

Council of Science Editors:

Martinez D. Individual differences in signed word learning among hearing adults. [Masters Thesis]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/59167

4. Remick, Olga V. Learning to attend: Measuring sequential effects of feedback in overt visual attention during category learning.

Degree: PhD, Psychology, 2015, Georgia Tech

 Trial-level evidence for feedback sensitivity in fixations during category learning has been previously described as weak. In this dissertation, steps were taken to overcome some… (more)

Subjects/Keywords: Eye-movements; Category learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Remick, O. V. (2015). Learning to attend: Measuring sequential effects of feedback in overt visual attention during category learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54397

Chicago Manual of Style (16th Edition):

Remick, Olga V. “Learning to attend: Measuring sequential effects of feedback in overt visual attention during category learning.” 2015. Doctoral Dissertation, Georgia Tech. Accessed December 11, 2019. http://hdl.handle.net/1853/54397.

MLA Handbook (7th Edition):

Remick, Olga V. “Learning to attend: Measuring sequential effects of feedback in overt visual attention during category learning.” 2015. Web. 11 Dec 2019.

Vancouver:

Remick OV. Learning to attend: Measuring sequential effects of feedback in overt visual attention during category learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Dec 11]. Available from: http://hdl.handle.net/1853/54397.

Council of Science Editors:

Remick OV. Learning to attend: Measuring sequential effects of feedback in overt visual attention during category learning. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54397

5. Thompson, Vanessa Marie. Marginal Bayesian parameter estimation in the multidimensional generalized graded unfolding model.

Degree: PhD, Psychology, 2014, Georgia Tech

 The Multidimensional Generalized Graded Unfolding Model (MGGUM) is a proximity-based, noncompensatory item response theory (IRT) model with applications in the context of attitude, personality, and… (more)

Subjects/Keywords: Estimation; Item response theory

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APA (6th Edition):

Thompson, V. M. (2014). Marginal Bayesian parameter estimation in the multidimensional generalized graded unfolding model. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53411

Chicago Manual of Style (16th Edition):

Thompson, Vanessa Marie. “Marginal Bayesian parameter estimation in the multidimensional generalized graded unfolding model.” 2014. Doctoral Dissertation, Georgia Tech. Accessed December 11, 2019. http://hdl.handle.net/1853/53411.

MLA Handbook (7th Edition):

Thompson, Vanessa Marie. “Marginal Bayesian parameter estimation in the multidimensional generalized graded unfolding model.” 2014. Web. 11 Dec 2019.

Vancouver:

Thompson VM. Marginal Bayesian parameter estimation in the multidimensional generalized graded unfolding model. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Dec 11]. Available from: http://hdl.handle.net/1853/53411.

Council of Science Editors:

Thompson VM. Marginal Bayesian parameter estimation in the multidimensional generalized graded unfolding model. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53411

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