Displaying results 1 - 9 of 9 (Go to Advanced Search)
Project
Description: Mathematical thinking is in high demand in the global market, but approximately six percent of school-age children across the globe experience math difficulties (Shalev, et al., 2000).
Project
Description: This meta-analysis examined effects of intervention on the level and trend of text-writing sequences of students with disabilities and writing difficulties, in addition to potential moderating effects related to student demographics (i.e., disability status, age, gender, and race) and writing task (i.e., sentence, essay, and narrative).
Project
Description: The purpose of this project was to develop a small-group literacy intervention for kindergarteners who are at-risk for reading and writing difficulties.
Dataset
Part of Project: The Home Math Environment and Children's Math Achievment: A Meta-Analysis
Description: The data are in long form, with some studies having multiple lines and includes a sample of children ranging from 3.54 to 13.75 years old. The main effect size is the r, correlation coefficient, and the accompanying sample size is also included.
Dataset
Part of Project: Writing Sequences of Students with Disabilities: A Review Contrasting Level and Trend Effects
Description: This meta-analysis examined effects of intervention on the level and trend of text-writing sequences of students with disabilities and writing difficulties, in addition to potential moderating effects related to student demographics (i.e., disability status, age, gender, and race) and writing task (i.e., sentence, essay, and narrative).
Dataset
Part of Project: Reading RULES! Kindergarten (RRK)
Description: These data are for teachers in the RRK study who were randomized to a treatment or control condition.
Dataset
Part of Project: Reading RULES! Kindergarten (RRK)
Description: Data for student participants including achievement data and demographics. Dataset is in wide format.
Code
Home Math Environment and Children's Math Achievement Meta-Analysis R code using the Metafor package
Part of Project: The Home Math Environment and Children's Math Achievment: A Meta-Analysis
Description: This code was written in R version 3.5.3 using the metafor package (Viechtbauer, 2010). First the dataset is called in, then the variables are converted to the correct formats for analysis, then the escalc() function is used to calculate an overall Fisher's Z effect size, which is then converted to an R correlation coefficient.
Code Type: Analysis
Document
Part of Project: Reading RULES! Kindergarten (RRK)
Description: Codebook for teacher and student data.
Document Type: Codebook
