This book introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression and machine learning and helps you develop skills such as R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux shell, version control with GitHub, and reproducible document preparation with R markdown.
This Shiny App is to provide a user-friendly interface for users to conduct item analysis based on Classical Test Theory (CTT). Item analysis is used for examining responses to individual test items in order to assess the quality of items and of the test as a whole. It is valuable in improving items or eliminating poorly written or ambiguous item. This Shiny App provides several strategies used for item analysis, including reliability estimates, item difficulty, item discrimination (i.e.,item total correlation).
This is one page of a series of tutorials for using R in psychological research. Much of material has also covered been covered in number of short courses or in a set of tutorials for specific problems.
Psychometrics is concerned with theory and techniques of psychological measurement. Psychometricians have also worked collaboratively with those in the field of statistics and quantitative methods to develop improved ways to organize, analyze, and scale corresponding data. Since much functionality is already contained in base R and there is considerable overlap between tools for psychometry and tools described in other views, particularly in SocialSciences, we only give a brief overview of packages that are closely related to psychometric methodology.
Lista de paquetes relacionados con psicometría
This page is devoted to teaching others about psychometric theory as well as R. It consists of chapters of an in progress text as well as various short courses on R.
This course is designed to introduce you to and help you become familiar with quantitative methodologies critical to your development as a social scientist. The introductory methods course has two primary aims. First, students will be introduced to quantitative methodology that researchers and policymakers use in answering social, political and economic questions. Second, the course will equip students to use one or more of the discussed techniques in their MSc dissertation.
By the end of the course, you should be able to understand basic research methods, apply them to real world problems and evaluate their use in published research. Students will also acquire competency in performing statistical analyses using a popular statistical program (R).
The first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications, books, dissertations, websites, and journal articles, while enjoying the simplicity of Markdown and the great power of R and other languages.