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  • Dr. Sarah G. Wood
  • Dana Santangelo
  • Dr. Fotena Zirps

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The Home Math Environment and Children's Math Achievment: A Meta-Analysis
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).
Investigators: Mia C. Daucourt, Dr. Amy R. Napoli, Dr. Jamie M. Quinn, Dr. Sarah G. Wood, Sara A. Hart
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Open science prevalence and predictors in scientific literature on reading
Description: This study is a meta-scientific systematic review of published research literature in the content area of reading in order to estimate the prevalence of participation in key open science practices amongst authors publishing on this topic. This study is a conceptual replication and extension of previous studies by Cook et al.
Investigators: Christine White, Stephanie Estrera, Emma Friedmann, Dana Santangelo, Cristian Vazquez, Chris Schatschneider
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Meta-Analysis Codebook of Final Articles with Effect Sizes, Sample Sizes, and Moderators
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.
Investigators: Dr. Amy R. Napoli, Dr. Jamie M. Quinn, Dr. Sarah G. Wood, Mia C. Daucourt, Sara A. Hart
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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.
Investigators: Dr. Amy R. Napoli, Dr. Jamie M. Quinn, Dr. Sarah G. Wood, Mia C. Daucourt, Sara A. Hart
Code Type: Analysis
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Longitudinal Study on Reading and Writing Codebook/Data Guide
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.
Investigators: Yusra Ahmed, Richard Wagner, Dr. Fotena Zirps
Document Type: Codebook
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Content Type

  • Project (2)
  • Code (1)
  • Dataset (1)
  • Document (1)

Constructs

  • Home Experiences (1)
  • Math (1)

Assessments

Participant Type

  • Children (1)

Special Populations

Educational Environments

  • Home Learning Environment (1)

Project Methods

  • Meta-analysis (1)
  • Systematic Review (1)

Developmental Designs

  • Cross-Sectional (2)
  • Individual Differences (1)
  • Longitudinal (1)

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  • [x] Dr. Sarah G. Wood (3)
  • [x] Dana Santangelo (1)
  • [x] Dr. Fotena Zirps (1)
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Organizations

  • Florida Center for Reading Research (3)
  • Florida State University (3)
  • University of Nebraska Department of Child Youth and Family Studies (1)

This repository is a collaboration between the FSU Department of Psychology, the Florida Center for Reading Research, and the FSU Libraries. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

On March 25, 2025, the NIH requested that we post this text: "This repository is under review for potential modification in compliance with Administration directives."

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