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This course is currently in session. If you register now you will get instant access to the remainder of the livestream online discussion. The links to watch the asynchronous video will be provided on February 21st.

LIVE STREAM – 4-day Statistics Short Course

Seminar Overview:

An introductory 4-day course in the application of psychometrics. Participants should be proficient specific to the material covered in a two-semester graduate-level social science statistics course sequence.

Seminar Topics:

  • Measurement and statistical concepts specific to psychometrics
  • Scaling, scaling models & scale development – stimulus, response and subject centered
  • Validity – conceptual and statistical aspects necessary for evidential arguments
  • Introduction to Factor analysis – traditional, IRT and SEM-based approaches/connections
  • Reliability – classical and modern approaches to estimation of score reliability
  • Introduction to Item Response Theory

Seminar Description:

Psychometrics is defined as the science of evaluating the characteristics of tests or other devices designed to measure psychological attributes of people. Tests are broadly defined as devices for measuring ability, aptitude, achievement, attitudes, interests, personality, cognitive functioning, and mental health. Application of psychometrics to psychology and social/behavioral science constitutes an organized effort to (a) properly use theory-based measurement procedures for the development of tests and other measurement instruments for inter- and intraindividual research designs and (b) incorporate current best practices for applying measurement theory, item/scale development, reliability estimation (classical and modern), factor analysis/IRT and establishing statistical evidence of score validity through a unified approach. advance knowledge in psychological and sensory processes. Participants will receive an electronic copy of all course materials, including lecture slides, practice datasets, software scripts, relevant supporting documentation, and recommended readings. Participants will also have access to a video recording of the course.

Instructor: Larry Price, Ph.D.

Larry Price, Ph.d. is a Professor of Psychometrics & Statistics and was previously Director of the Office of Data Analytics & Methodology at Texas State University for 13 years. Between 1999 and 2002, Dr. Price was employed at The Psychological Corporation in San Antonio as a Senior Psychometrician/Statistician where his work focused on improving the psychometric properties of the Wechsler Scales of Intelligence Memory (e.g., WISC-III, WISC-IV, WAIS-III, WMS-III, and WPPSI-III), and Achievement (WIAT-II) and other psychological measures such as the Beck Depression Inventory (BDI) and Clinical Evaluation of Language Fundamentals (CELF-IV). His research interests include the theoretical development and testing of Bayesian and non-Bayesian psychometric models in psychological and neuropsychological research (neuroimaging network analysis), theoretical development, testing, and refinement of classical and modern psychometric methods in the behavioral sciences, development of dynamic multivariate time series models for the psychological, social and neurosciences. Before working at Psychological Corporation, he worked at Emory University from 1986 to 1999 as a Biostatistician and Psychometrician in the School of Medicine. Funding mechanisms for Dr. Price’s work include NIH, NSF, DOE, and private organizations.

APA Continuing Education Credits:

This course provides 22 credit hours for continuing education. Stats Camp Foundation is approved by the American Psychological Association to sponsor continuing education for psychologists. Stats Camp Foundation maintains responsibility for this program and its content.

Seminar Includes:

Materials, downloads, recorded course video viewable for up to one year.

Learning Objectives:

  • Acquire a basic understanding of the role of psychometrics as applied to social and behavioral sciences.
  • Develop a clear understanding of the conceptual and theoretical basis of measurement theories, models, and statistical concepts specific to psychometrics.
  • Acquire knowledge of how to properly apply psychometric techniques such as scale development, item analysis/refinement, score reliability and statistical validity.
  • Gain knowledge of how to apply factor analysis using traditional and structural equation modeling approaches related to test and scale development and evaluation.
  • Gain knowledge of how to apply generalizability theory for estimating variance components and score reliability when classical test theory model is inadequate.
  • Acquire basic knowledge of how and why to apply item response theory for scaling test data and test development and evaluation.

Seminar Prerequisites:

Required:

  • Intermediate proficiency in basic statistical theory as would be gained in a 1st year graduate course.

Not required but advantageous:

  • Limited experience (e.g., graduate-level course) with classical measurement theory and concepts.

No level of proficiency beyond basic awareness is assumed for skills related to:

  • Advanced mathematical or statistical topics such as matrix algebra.

Software and Computer Support:

Participants need to bring a laptop computer with Wi-Fi capabilities. Students should have access to IBM SPSS, version 21.0 or higher and Mplus, version 7.1 or higher and R.

All statistical software used at Stats Camp will be available, free to participants, on our SMORS (statistical modeling on remote servers) system for the duration of camp.

Day 1  
9:00-9:30 Welcome and introductions
9:30-10:15 Measurement & statistical concepts
10:15-10:30 Break
10:30-11:30 Scaling and scaling models – achievement, ability, attitude & perception
11:30-12:30 Lunch break
12:30-1:30 Techniques for item and test development, evaluation & refinement
1:30-3:00 Validity – criterion, content & construct considerations
3:15-5:00 Statistical aspects of the score validation process
Day 2
9:00-10:00 Factor analysis – foundations, types and estimating factor models using exploratory and confirmatory approaches – part 1
10:00-11:30 Factor analysis – a unified model for test theory and application, estimating factor models using structural equation modeling – part 2
11:30-12:30 Lunch break
12:30-1:30 Computer exercises – Common Factor Analysis using traditional algorithms for applied factor analysis – exploratory and confirmatory strategies in test development
1:30-3:30 Higher-order, Bifactor, and multidimensionality with computer exercises
Day 3
9:00-10:00 Reliability of test scores – foundations/application of classical test theory; Using/applying structural equation modeling and IRT for score reliability estimation; Rater reliability models
10:00-11:00 Contemporary approaches to reliability estimation (factor analysis & IRT)
11:00-12:00 Introduction to Item Response Theory – theory and applications for applied psychometrics; Relationship to structural equation modeling
12:00-1:00 Lunch break
1:00-3:00 Computer exercises – Item Response Theory & Factor Analysis for scale construction and refinement
3:15-5:00 * Individual Consultations (optional)
Day 4
9:00-10:30 Introduction to Measurement Invariance/Differential Item & Test Functioning – example programs for analyses and interpretation
10:30-10:45 Break
10:45-12:00 Introduction to generalizability theory – G-studies and D-studies
12:00-1:00 Lunch Break
1:00-2:00 Generalizability – estimating reliability of rater data
2:00-3:00 Normative scores – development and use

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