Магистратура
2024/2025
Углубленные методы в психометрике и анализе данных
Статус:
Курс по выбору (Обучение и оценивание как наука)
Направление:
37.04.01. Психология
Кто читает:
Департамент образовательных программ
Где читается:
Институт образования
Когда читается:
2-й курс, 2, 3 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для всех кампусов НИУ ВШЭ
Преподаватели:
Грачева Дарья Александровна
Прогр. обучения:
Обучение и оценивание как наука
Язык:
английский
Кредиты:
6
Контактные часы:
56
Course Syllabus
Abstract
This course aims to introduce advanced statistical methods and statistical models which are used in psychometrics and data analysis of psychological, sociological and educational data. Students will learn different approaches to latent variables analysis, such as Confirmatory Factor Analysis (CFA) and some models within Item Response Theory (IRT) framework such as bifactor IRT models etc. Topics of structural equation modelling, analysis of mediated and moderated relations between latent variables will be also introduced. Course continues with discussion of generalized linear models and extension of this models – generalized linear mixed effects models (GLMM). Different types of GLMM, their assumptions and application in social data analysis will be reviewed. At the end of the course some models with discrete latent variables (Latent Class Analysis, Cognitive Diagnostic Models) will be discussed. During the course students learn to select, apply and discuss the results of statistical models appropriate for addressing a given research problem.
Prerequisites:
1) Basic knowledge of statistics (especially regression analysis and factor analysis)
2) Basic knowledge of Item Response Theory (recommended, but now required)
3) Experience of working with base R.