APA Acredited Statistics Training
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LIVE STREAM – 4-day Statistics Short Course

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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. PStat is the Director of the Data Analytics & Methodology at Texas State University. This university-wide role involves supervising a team of quantitative methodologists in conceptualizing and writing the analytic segments of large-scale competitive grant proposals for funding agencies such as the Department of Education/Institute of Education Sciences, National Science Foundation, National Institutes of Health, National Institute on Standards, and the Department of Defense in collaboration with interdisciplinary research teams. His research has been funded by agencies such as the Department of Education/Institute of Education Sciences, National Science Foundation, National Institutes of Health, National Institute on Standards, and the Department of Defense.

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APA Continuing Education Credits:

This course offers ? hours of Continuing Education Credits. Yhat Enterprises, LLC is approved by the American Psychological Association to sponsor continuing education for psychologists. Yhat Enterprises, LLC 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 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.
  • 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.

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
9:30-10:30 Measurement & statistical concepts
10:30-10:45 Snack and refreshment break
10:45-12:30 Scaling and scaling models – achievement, ability, attitude & perception
12:30-1:30 Lunch break
1:30-3:00 Techniques for item and test development, evaluation & refinement
3:00-3:15 Snack and refreshment break
3:15-5:00 Validity – criterion, content & construct considerations
Day 2
9:00-10:45 Statistical aspects of the score validation process
10:45-11:00 Snack and refreshment break
11:00-12:30 Factor analysis – foundations, types and estimating factor models using exploratory and confirmatory approaches – part 1
12:30-1:30 Lunch break
1:30-3:00 Factor analysis – a unified model for test theory and application, estimating factor models using structural equation modeling – part 2
3:00-3:15 Snack and refreshment break
3:15-5:00 Individual Consultations (alternatively start reliability presentation)
Day 3
9:00-10:45 Reliability of test scores – foundations/application of classical test theory; Using/applying structural equation modeling and IRT for score reliability estimation
10:45-11:00 Snack and refreshment break
11:00-12:30 Introduction to Item Response Theory – theory and applications for applied psychometrics; Relationship to structural equation modeling
12:30-1:30 Lunch break
1:30-3:00 Introduction to generalizability theory
3:00-3:15 Snack and refreshment break
3:15-5:00 Individual Consultations (or continue presentation of material)

 

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