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Project
Description: The Western Reserve Reading and Math Project (WRRMP) is a NIH funded longitudinal study on child development. The project has collected data annually for 15 years, with data on approximately 450 twin pairs collected during this time. The project has had several focal points throughout its history.
Project
Description: The data within this project comprise a four year longitudinal study assessing various aspects of literacy including decoding, fluency, vocabulary, reading comprehension, listening comprehension, working memory and writing. Participants were tested on all measures once a year, approximately one year apart.
Project
Description: Project Goals:
The first goal will fill a CUREs gap by creating self-supporting and sustainable protein-centric
CUREs. The second goal will use this protein-centric CUREs community to examine two critical
aspects of a CURE: 1) the impact of the length of CUREs (course long CUREs (cCUREs) or shorter, modular
Dataset
Part of Project: Western Reserve Reading and Math Project
Description: This dataset contains all longitudinal data for the entirety of the WRRMP. This includes 10 waves worth of twin data, with extensive reading, math, behavioral, and environmental measures. Due to the twin nature of the data, data is presented as both long and wide, with each twin represented twice within the dataset.
Dataset
Part of Project: Longitudinal Study on Reading and Writing at the Word, Sentence, and Text Levels
Description: This dataset is longitudinal in nature, comprising data from school years (2007/2008-2010/2011) following students in grade 1 to grade 4. Measures were chosen to provide a wide array of both reading and writing measures, encompassing reading and writing skills at the word, sentence, and larger passage or text levels.
Document
Part of Project: Longitudinal Study on Reading and Writing at the Word, Sentence, and Text Levels
Description: This document provides information regarding the naming of variables within the dataset, as well as information regarding the specific tests and subtests included in said dataset.
Document Type: Codebook
