Public Health Documents

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Public Health Research

Data Entry Guidelines for Excel - Dana Hince PhD

This file outlines the best practices for data entry in Excel to minimize errors and improve data analysis. It provides structured guidance on how to format your spreadsheets for compatibility with statistical analysis software. Ideal for health researchers and data analysts seeking to ensure accurate data capture and facilitate analysis.

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Public Health Research

OnCore Electronic Case Report Forms eCRFs Overview

This file provides detailed instructions and benefits of using OnCore Electronic Case Report Forms (eCRFs). It outlines how these forms enhance data collection for researchers. Ideal for researchers using OnCore to streamline their data entry processes.

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Public Health Research

ME Lab Faculty Collaboration Request Form

Access the ME Lab Faculty Collaboration Request Form to initiate your research project collaboration. This comprehensive form ensures all necessary details and approvals are addressed. Perfect for faculty members seeking to engage with the ME Lab for innovative research opportunities.

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Public Health Research

Sample Informed Consent for Research Participation

This form is an informed consent for participating in a research study at Missouri State University. It outlines the purpose, procedures, risks, and benefits of the study. By signing this form, participants agree to take part in the study.

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Health Insurance Programs

Anthem MediBlue Service Disenrollment Form 2023

This document serves as the Anthem MediBlue Service (PPO) Individual Disenrollment Form for the year 2023. It guides members on how to disenroll and provides essential instructions and eligibility requirements. Ensure to provide all required information and follow the submission steps.

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Public Health Research

Fighting Fake News Workshop Report

This report details the findings from the Fighting Fake News workshop held on March 7, 2017. It explores the challenges of defining fake news and potential solutions. The document serves as a foundation for interdisciplinary discussions on misinformation.

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Public Health Research

Prediction of Bed Form Height in Channels

This file presents a comparative analysis of various prediction methods for bed form dimensions in alluvial channels. It details experimental findings using data from the UK Flood Channel Facility. The study evaluates the accuracy of several established formulas for predicting bed form heights in both straight and meandering channels.

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Healthcare Policy

USAG Yongsan-Casey Employee Recognition Policy

This document outlines the policy for recognizing employees at US Army Garrison Yongsan-Casey. It includes references, the commander's intent, and the execution plan for the employee recognition program. Detailed criteria and procedures for various employee awards are provided.

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Public Health Research

Qualtrics Guide for University Research Projects

This file serves as a comprehensive guide for using Qualtrics in research projects at Middlesex University. It covers important aspects like participant consent and data collection methods. Suitable for both staff and students involved in research.

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Public Health Research

Sample Online Consent Form for TWU Research

This file contains a sample online consent form used in research studies at Texas Woman's University. It outlines the study's purpose, procedures, risks, and participant rights. Researchers can utilize this template to guide their consent process for human subject research.

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Public Health Research

Material Transfer and Data Agreement Form

This form is for requesting and managing material and data transfers. It provides guidelines for the proper handling of non-disclosure agreements as well. Ideal for Sacramento State personnel and external entities.

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Public Health Research

Circuits for Integer Factorization Proposal

This document presents a proposal by Daniel J. Bernstein discussing circuits for integer factorization. It covers advancements in algorithms and provides detailed analysis for computational efficiency. Ideal for researchers and practitioners in computational number theory.