POSTPONED
A Paradigm Shift in Clinical Research and Education: The P-value Controversy and the End of Statistical Significance?

POSTPONED

Given guidance and recent reports related to the novel coronavirus disease (COVID-19), this event has been postponed.

We hope to reschedule the symposium for later this year. As soon as new details are available, we will share them here.

We apologize for any inconvenience.

What does the p-value controversy mean for clinical research?

The deep controversy surrounding the use and misuse of p-values and statistical significance is evident in the decision by the American Statistical Association to issue a policy statement on the matter in 2016. The statement marked the first occasion the Association has taken a position on a specific matter of statistical practice since its founding in 1839.

This Tufts CTSI symposium, co-sponsored by the Tufts Data Intensive Studies Center (DISC),  aims to inform clinician researchers and statisticians regarding the principles covered in the statement as well as the controversy over the proper use and interpretation of the p-value. Distinguished panelists will speak on use of p-values from their multiple perspectives to reflect the landscape of opinions and provide guidance for investigators and educators going forward. They include scientists, statisticians, epidemiologists, and statistical advisors to prominent journals and policy organizations, with expertise in statistics, genetics, communication, nutrition, obesity, cardiovascular disease, and drug approval.

Learning objectives:

  • Understand the rationale behind the ASA statement that “No single index [i.e., p-value] should substitute for scientific reasoning.
  • Discuss the role that p-values have had on reproducibility and replication and the proposed remedies.
  • Apply alternative remedies for dealing with uncertainty in clinical research and education.


Panelists

John P.A. Ioannidis, MD, DSC

C.F. Rehnborg Chair in Disease Prevention and Professor at Stanford University
Author of “Why Most Published Research Findings are False,” accessed more than three million times. His recent JAMA viewpoint is subtitled “Do Not Abandon Significance.” Dr. Ioannidis has published nearly 1,000 papers and is one of the 10 most-cited scientists worldwide.

David Allison, PhD

Dean and Provost of the Indiana University School of Public Health
Author of “A Tragedy of Errors: Mistakes in Peer-reviewed Papers are Easy to Find but Hard to Fix, Report” and committee member of the National Academies of Sciences, Engineering, and Medicine report, “Reproducibility and Replicability in Science.”

David Harrington, PhD

Professor of Biostatistics, Emeritus, Harvard T.H. Chan School of Public Health
Co-Author of the 2019 New England Journal of Medicine article, “New Guidelines for Statistical Reporting in the Journal.” Dr. Harrington is also the principal investigator of the Statistical Coordinating Center for the Cancer Care Outcomes Research and Surveillance (CanCORS) Consortium and the project leader of the Biostatistics Core and Director of the Biostatistics Research Program in the Dana-Farber/Harvard Cancer Center (DF/HCC).

Allen Schirm, PhD

Recently retired from Mathematica Policy Research
Co-Author of the 2019 The American Statistician editorial, “Moving to a World Beyond ‘p<0.05’.” He and Dr. Ron Wasserstein recently discussed their recommendations on statistical inference at the United States Conference on Teaching Statistics.

 

Details

Tuesday, April 7
8:30-11:30AM
Jean Mayer Human Nutrition Research Center on Aging (HNRCA)
711 Washington Street, Boston, MA 02111

All are welcome to attend, especially:

  • Clinician researchers and investigators leading clinical trials.
  • Statisticians working with and educating clinical investigators.

Registration

Space is limited. Please register to attend.

 

About Tufts CTSI Events

Tufts CTSI’s Professional Education programs provide non-degree continuing education and training for clinical and translational research professionals from all Tufts CTSI partners and beyond.

Course enrollment priority is given to researchers from Tufts CTSI partner institutions. If your participation needs to be approved by your supervisor or a person responsible for your time release, you may provide their contact information when you register for the program.

This course is provided free of charge, and was supported by the National Center for Advancing Translational Sciences, National Institutes of health, Award Number UL1TR002544.  The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

 

Seminars & Workshops
Center for Quantitative Methods and Data Science Seminar 2021: Elena Naumova, PhD, MS

How can data help us to better understand and respond to the synchronization of infectious outbreaks?

The March seminar of the Center for Quantitative Methods and Data Sciences (QM&DS), in partnership with the Biostatistics, Epidemiology and Research Design (BERD) Center at Tufts CTSI and the Data-Intensive Studies Center (DISC) at Tufts University, is Wednesday, March 31, 2:00-3:00PM via Zoom. The topic of this month’s webinar is To Everything There is a Season: Synchronization of Infectious Outbreaks, presented by Elena Naumova, PhD.

A marked seasonality in many infections, like influenza or salmonellosis, is a well-known phenomenon. When we observe a pronounced seasonal pattern, it gives us a reason to expect high predictability of high or low disease incidence periods in a calendar year. With the expansion of national and global surveillance systems, the opportunities to better understand the local, regional, and global temporal fluctuations are also growing. As we learn more about the seasonality of many infections, it is reasonable to expect that some will co-occur. Yet, patterns of co-occurrences and factors driving such synchronization remain elusive.

In this talk, Dr. Naumova will demonstrate the methodology developed to assess the extent, lag, and directionality of seasonal synchronization. Dr. Naumova will provide several examples using national databases, such as the CDC’s Foodborne Disease Active Surveillance Network (FoodNet), National Outbreak Reporting System (NORS), and the FluNet supported by the WHO to illustrate seasonal synchronizations among foodborne infections and the challenges of time-referenced surveillance data. The modeling approaches include the trend-adjusted mixed effects nonlinear harmonic regression models and the delta-method to derive the estimates and confidence intervals for the seasonal peak timing and amplitude, allowing us to build local, regional, and global disease calendars. The methodological rigor, standardization, and data harmonization across surveillance systems are enabling comprehensive characterization of disease seasonality and serve as a pathway for implementing the Precision Public Health, Nutrition, and Medicine principles to tailor prevention and intervention strategies.

Faculty

Elena Naumova, PhD is Professor and Chair of the Division of Nutrition Epidemiology and Data Science at the Friedman School of Nutrition Science and Policy at Tufts University. Dr. Naumova’s area of expertise is in developing methodology for modeling of transient processes with applications in environmental epidemiology, nutrition, infectious diseases, and public health. As a mathematician by training, she designs statistical, computational and mathematical models to characterize and forecast infectious outbreaks. Dr. Naumova is using large-scale data sources to study infections sensitive to climate variations and extreme weather. She led research programs in emerging biomedical fields of epidemiology, immunogenetics, nutrition and growth, nationally and internationally to set new standards for public health investigations. Dr. Naumova is Editor-in-Chief for the Journal of Public Health Policy (Nature Publishing Group). She is currently funded by the NSF to develop ways to train data-savvy workforce, highlight advancements and challenges of data revolution, share examples where the data analytics and data visualizations enhance our knowledge and help to find solutions to wicked problems. Dr. Naumova hopes to stir the discussion on how data scientists have to rethink and reframe the state-of-the-art methodology to enable the discovery of emerging trends in global health fields.

Details

Wednesday, March 31, 2021, 2:00-3:00PM, online via Zoom

Registration

To attend, please enroll here via Tufts CTSI I LEARN.

 

CANCELLED
Center for Quantitative Methods and Data Science Seminar 2021: Sara Lodi, PhD, MS

CANCELLED

This event has been cancelled. We apologize for any inconvenience, and hope to reschedule Dr. Lodi’s seminar soon.

What is the long-term effect of direct antiviral agents for Hepatitis C?

The April seminar of the Center for Quantitative Methods and Data Science (QM&DS), in partnership with the Biostatistics, Epidemiology and Research Design (BERD) Center at Tufts CTSI and the Data-Intensive Studies Center (DISC) at Tufts University, is Wednesday, April 21, 2:00-3:00PM via Zoom. The topic of this month’s webinar is What is the Long-term Effect of Direct Antiviral Agents for Hepatitis C? A Causal Inference Approach Using ‘Big Data,’ presented by Sara Lodi, PhD.

The advent of direct-acting antiviral agents (DAAs) in 2011 revolutionized hepatitis C virus (HCV) treatment: based on clinical trials and real world data, approximately 95% of patients treated with DAA achieved a sustained virological response equivalent to cure. However, even after cure is achieved, the risk of hepatic and extra-hepatic disease remains. Our understanding of post-DAA clinical outcomes is based on clinical trials with relatively short follow-up and selected participants. However, the extent to which DAA impacts extra-hepatic morbidity in the long-term and in heterogenous populations is unknown. Electronic health records collected in routine clinical practice provide a unique opportunity to estimate the long-term benefits of DAA treatment and to assess the need for post-DAA clinical management.

In this talk, Dr. Sara Lodi will discuss how to design an observational study to estimate the effect of DAA on kidney function using the target trial approach. She will also describe how to apply and interpret the results of the parametric g-formula, a causal inference method that provides consistent estimates in the presence of treatment-confounding feedback. Dr. Lodi will present preliminary results using electronic health records from Boston Medical Center and the HepCAUSAL collaboration.

 

Faculty

Sara Lodi, PhD is an Assistant Professor in Biostatistics at Boston University School of Public Health. She obtained her PhD in Medical Statistics at the London School of Hygiene and Tropical Medicine in 2009. Her research focuses on clinical trials, clinical epidemiology and comparative effectiveness research using routinely collected heath data, particularly in the area of infectious disease and substance use. Methodologically, she focuses on statistical techniques for causal inference to estimate effects of interventions along the HIV continuum of care. She has published many articles on behalf of large international collaborations of HIV cohorts such as CASCADE, COHERE, URBAN ARCH and the HIV-CAUSAL Collaboration.

Details

This event is cancelled.

 

 

Seminars & Workshops
Center for Quantitative Methods and Data Science Seminar 2021: Tanya Karagiannis, MS

How do centenarians delay and defy aging?

The Center for Quantitative Methods and Data Science, in partnership with the Biostatistics, Epidemiology and Research Design (BERD) Center and the Data-Intensive Studies Center (DISC) will host a virtual seminar series on a Wednesday each month from 2:00-3:00PM.

The session on Wednesday, January 20 will feature Research Assistant and PhD Candidate Tanya Karagiannis, MS. She will give a talk titled Analysis of Single Cell Transcriptomics Data as it Relates to Aging and Longevity.

Abstract

Studies of aging have shown a gradual decline in the immune system, such that people experience age-related disabilities and diseases as well as differences in immune population composition and functions over time. However, a rare population of individuals who reach 100 years of age known as centenarians, experience delay in age-related disabilities and diseases and in fact live the majority of their lives in good health. In order to investigate how centenarians delay and defy aging, we utilize single cell transcriptomic methods to investigate longevity related differences in the peripheral blood immune system of centenarians.

Single cell level transcriptomic data has allowed for the profiling of thousands of cells to characterize cell states and populations in specific tissues. More specifically, these methods can be used to identify rare populations and assess transcriptional similarities and differences within a population of cells. We describe integrated analyses using four single cell RNA-sequencing datasets that we conducted to investigate compositional and gene expression differences in immune populations of centenarians and younger age controls (20-80 years).

Early findings demonstrate gene expression differences between centenarians and younger age controls that are specific to populations of cells. We also find centenarians not only have cell type specific compositional differences but overall have more cell type diversity than younger age controls.

Faculty

Tanya Karagiannis is a Research Assistant at Tufts Medical Center in the Institute for Clinical Research and Health Policy Studies, working with Dr. Paola Sebastiani. She has an MS in Bioinformatics from Boston University where she is also continuing her PhD in Bioinformatics under the advisement of Dr. Paola Sebastiani and Dr. Stefano Monti.  Her research focus is in the application and development of single cell transcriptomic methods utilizing machine learning and Bayesian statistics, with interest in multi-omics as well.

Details

Date: Wednesday, January 20, 2020, 2:00-3:00PM

Registration

To attend, please enroll via Tufts CTSI I LEARN here.

 

Seminars & Workshops
Center for Quantitative Methods and Data Science Seminar 2021: Thomas Stopka, PhD, MS

How can data help us to better understand and respond to the opioid crisis?

The Center for Quantitative Methods and Data Science, in partnership with the Biostatistics, Epidemiology and Research Design (BERD) Center and the Data-Intensive Studies Center (DISC) will host a virtual seminar series on a Wednesday each month from 2:00-3:00PM.

The session on Wednesday, February 17 will feature Associate Professor Thomas Stopka, PhD, MS. He will give a talk titled Spatial Epidemiological Analysis and Modeling of Opioid Decedent Data.

Abstract

The current opioid crisis has contributed to precipitous increases in opioid use disorder, fatal overdoses, and infectious diseases. Opioid-related overdoses alone have increased five-fold during the past two decades in Massachusetts. Decedent data, available through the Massachusetts Registry for Vital Records and Statistics, provide a valuable resource to better understand and respond to the opioid crisis. Together with his GIS and spatial epidemiology team, Dr. Thomas Stopka has explored the spatial distribution of fatal overdoses across the state to identify high-risk locations and inform targeted public health responses.

In this presentation, Dr. Stopka will provide an overview of his work, with a focus on geo-mapping, spatial epidemiological analyses, statistical modeling, and geographically weighted regression analyses. He will highlight fatal overdose hotspots, factors associated with overdose, spatial access to services, and unique approaches to modeling the risk landscape.

Faculty

Thomas Stopka, MS, PhD is is an associate professor with the Department of Public Health and Community Medicine at Tufts University School of Medicine and Tufts Clinical and Translational Science Institute (CTSI). He has contributed to and led numerous mixed methods, interdisciplinary, and translational studies focused on the intersection of opioid use disorder, overdose, and infectious disease since 1999. Dr. Stopka has employed geographic information systems (GIS), spatial epidemiological, qualitative, biostatistical, and laboratory approaches in multi-site, multi-investigator studies and public health interventions to better understand and curb the opioid syndemic. He currently leads and contributes to several studies funded by the NIH, CDC, SAMHSA, state and local public health departments, and private and philanthropic agencies, with a focus on development and implementation of evidence-based interventions among opioid users in New England. Dr. Stopka is Co-Chair of the Tufts research priority group focused on equity in health, wealth, and civic engagement. He teaches courses in GIS and spatial epidemiology, research methods for public health, and epidemiology.

Details

Date: Wednesday, February 17, 2021, 2:00-3:00PM

Registration

To attend, please enroll via Tufts CTSI I LEARN here.

 

Seminars & Workshops
Center for Quantitative Methods and Data Science Seminar: Karl Broman, PhD

Interested in learning how to make your data analysis and other scientific computations reproducible?

The Center for Quantitative Methods and Data Science, in partnership with the Biostatistics, Epidemiology and Research Design (BERD) Center and the Data-Intensive Studies Center (DISC) will host a virtual seminar series on a Wednesday each month from 2:00-3:00PM.

The session on Wednesday, December 16 will feature Karl Broman, PhD. He will give a talk titled Steps Toward Reproducible Research.

Abstract

A minimal standard for data analysis and other scientific computations is that they be reproducible: that the code and data are assembled in a way so that another group can re-create all of the results (e.g., the figures and table in a paper). Adopting a workflow that will make your results reproducible will ultimately make your life easier; if a problem or question arises somewhere down the line, it will be much easier to correct or explain.

But organizing analyses so that they are reproducible is not easy. It requires diligence and a considerable investment of time: to learn new computational tools, and to organize and document analyses as you go. Nevertheless, partially reproducible is better than not at all reproducible. Just try to make your next paper or project better organized than the last. There are many paths toward reproducible research, and you shouldn’t try to change all aspects of your current practices all at once. Identify one weakness, adopt an improved approach, refine that a bit, and then move on to the next thing. Dr. Karl Broman will offer some suggestions for the initial steps to take towards making your work reproducible.

Faculty

Dr. Karl Broman is a Professor in the Department of Biostatistics & Medical Informatics at the University of Wisconsin-Madison. Dr. Broman is an applied statistician working on the genetics of complex diseases in experimental organisms. He develops the R package, R/qtl, has written a number of short tutorials useful for data scientists, and is very keen to develop tools for interactive data visualization (to view an example, click here).

Details

Date: Wednesday, December 16, 2020, 2:00-3:00PM

Registration

To attend, please enroll via Tufts CTSI I LEARN here.

 

CANCELLED
Center for Quantitative Methods and Data Science Seminar: Tanya Karagiannis, MS

This event is cancelled. We apologize for any inconvenience.

The Center for Quantitative Methods and Data Science, in partnership with the Biostatistics, Epidemiology and Research Design (BERD) Center and the Data-Intensive Studies Center (DISC) will host a Zoom seminar series on a Wednesday each month from 2:00-3:00PM.

The November session on Wednesday, November 11 will feature Tanya Karagiannis, MS. She will give a talk titled Analysis of Single Cell Transcriptomics Data as it Relates to Aging and Longevity.

Abstract

Studies of aging have shown a gradual decline in the immune system, such that people experience age-related disabilities and diseases as well as differences in immune population composition and functions over time. However, a rare population of individuals who reach 100 years of age known as centenarians, experience delay in age-related disabilities and diseases and in fact live the majority of their lives in good health. In order to investigate how centenarians delay and defy aging, we utilize single cell transcriptomic methods to investigate longevity related differences in the peripheral blood immune system of centenarians. Single cell level transcriptomic data has allowed for the profiling of thousands of cells to characterize cell states and populations in specific tissues. More specifically, these methods can be used to identify rare populations and assess transcriptional similarities and differences within a population of cells. We describe integrated analyses using four single cell RNA-sequencing datasets that we conducted to investigate compositional and gene expression differences in immune populations of centenarians and younger age controls (20-80 years). Early findings demonstrate gene expression differences between centenarians and younger age controls that are specific to populations of cells. We also find centenarians not only have cell type specific compositional differences but overall have more cell type diversity than younger age controls.

Faculty

Tanya Karagiannis is a Research Assistant at Tufts Medical Center in the Institute for Clinical Research and Health Policy Studies, working with Dr. Paola Sebastiani. She has an MS in Bioinformatics from Boston University where she is also continuing her PhD in Bioinformatics under the advisement of Dr. Paola Sebastiani and Dr. Stefano Monti. Her research focus is in the application and development of single cell transcriptomic methods utilizing machine learning and Bayesian statistics, with interest in multi-omics as well.

Details

Date: Wednesday, November 11, 2020, 2:00-3:00PM

Location: Zoom video conference.

Registration

To receive the link to the Zoom video conference, please register here.

 

Seminars & Workshops
Center for Quantitative Methods and Data Sciences Seminar: Cody Meissner, MD and Norma Terrin, PhD

The Center for Quantitative Methods and Data Sciences, in partnership with the Biostatistics, Epidemiology and Research Design (BERD) Center and the Data-Intensive Studies Center (DISC) will host a Zoom seminar series on a Wednesday each month from 2:00-3:00PM.

The October session on Wednesday, October 21 will feature Cody Meissner, MD, and Norma Terrin, PhD. They will speak about the promise of COVID-19 vaccines in controlling the pandemic.

Abstract

The discussion will cover approaches to SARS-CoV-2 vaccine development; emergency use authorization (EUA) vs. biologic license application (BLA); acceptable safety and effectiveness; unanticipated serious adverse reactions that occurred following introduction of previous vaccines; and vaccine trial sample size justification.

Faculty

Dr. Meissner is Professor of Pediatrics at Tufts University School of Medicine and Head of the Pediatric Infectious Disease Service at Tufts Medical Center. He is a Consultant to the Committee on Infectious Disease and an Associate Editor of the Red Book for the American Academy of Pediatrics. He has served as a member of the Advisory Committee on Infectious Diseases (ACIP) at the Centers for Disease Control and Prevention (CDC) and continues to advise CDC Work Groups. He presently serves as a member of the National vaccine Advisory Committee (NVAC) and as a member of the Vaccines and Related Biologic Products Advisory Committee (VRBPAC) for the Food and Drug Administration. He serves as a member of the Massachusetts Vaccine Purchasing Council. He has published over 250 papers on various aspects of infectious disease.

Dr. Terrin is the Scientific Director of the BERD Center at Tufts Clinical and Translational Science Institute (CTSI) and Professor at Tufts University School of Medicine. She has collaborated with clinical investigators, including infectious disease researchers, throughout her career, and she served as Statistics Editor at Clinical Infectious Diseases for 12 years.

Details

Date: Wednesday, October 21, 2020, 2:00-3:00PM

Location: Zoom video conference. To receive the Zoom link and passcode, please email Lori Lyn Price, MAS at lprice1@tuftsmedicalcenter.org.

 

 

Seminars & Workshops
Center for Quantitative Methods and Data Sciences Seminar: Karin Knudson, PhD

The Center for Quantitative Methods and Data Sciences, in partnership with the Biostatistics, Epidemiology and Research Design (BERD) Center and the Data-Intensive Studies Center (DISC) will host a Zoom seminar series on the fourth Wednesday of the month from 2:00-3:00PM.

The first session on Wednesday, September 23 will feature Karin Knudson, PhD, Senior Data Scientist with DISC. She will speak about the estimation of ataxia severity and disease classification from wearable sensor recordings.

Abstract

Wearable sensor data offer the potential for rich and interpretable descriptions of behavioral characteristics of ataxia and other neurodegenerative diseases. High quality behavioral biomarkers are important for understanding disease progression, assessing efficacy in clinical trials, and supporting early diagnosis and targeted interventions. In this talk we present methods for using accelerometer and gyroscope time series data from wearable sensors in order to accurately distinguish patients with ataxia from healthy controls and to estimate disease severity. We combine information from an autoregressive hidden Markov model variant and time-frequency analysis to create a flexible, extensible, and meaningful quantitative description of movement and to perform severity estimation and disease classification with short periods of data collection.

Faculty

Dr. Knudson is a Senior Data Scientist with the Tufts Data Intensive Studies Center (DISC). Her research has involved the development and application of methods from machine learning, Bayesian statistics, and compressive sensing, particularly to neural data. Before joining Tufts, she was a Research Fellow in the Department of Neurology at Massachusetts General Hospital and Harvard Medical School, and was previously the Chair of the Department of Mathematics, Statistics, and Computer Science at Phillips Academy. She completed her PhD in Mathematics at the University of Texas at Austin.

Details

Date: Wednesday, September 23, 2020, 2:00-3:00PM

Location: Zoom video conference. To receive the Zoom link and passcode, please email Lori Lyn Price, MAS at lprice1@tuftsmedicalcenter.org.

 

 

Meeting
Dissemination and Implementation Science Special Interest Group Meeting

Interested in learning more about implementation science and dissemination and implementation strategies?

You are invited to a virtual Dissemination and Implementation Science Special Interest Group Meeting on Tuesday, December 1, 10:00-11:00AM to present your research project, solicit feedback from other members, and receive advice from Tufts CTSI faculty leads Denise Daudelin, RN, MPH, and Sara Folta, PhD.

Even if you do not have a current project, you are welcome to join to learn more about this emerging field and hear from fellow researchers.

Details

Date: Tuesday, December 1, 10:00-11:00AM

Registration

To attend, please enroll here via Tufts CTSI I LEARN.

Meeting
Dissemination and Implementation Science Special Interest Group Meeting, February 3

Interested in learning more about implementation science and dissemination and implementation strategies?

You are invited to a virtual Dissemination and Implementation Science Special Interest Group Meeting on Wednesday, February 3, 1:00-2:00 PM to discuss Dr. Jana Leary’s research on implementing a social determinants of health screening in primary care outpatient settings.

The group will learn more about the research project and engage in a discussion about the research. The conversation will be facilitated by Tufts CTSI faculty leads Denise Daudelin, RN, MPH, and Sara Folta, PhD.

Even if you do not have a current project, you are welcome to join to learn more about this emerging field and hear from fellow researchers.

Details

Date: Wednesday, February 3, 1:00-2:00PM

Registration

To attend, please enroll here via Tufts CTSI I LEARN.

Seminars & Workshops
Evaluating Scientific Journal Articles

View the slides for this seminar (PDF).

View the article that will be discussed during this seminar (PDF).

 

What makes a journal article successful?

Join us for Evaluating Scientific Journal Articles and learn the questions you should ask yourself, whether reviewing journal articles or writing your own. This interactive seminar will be presented by Lori Lyn Price, MAS, Statistician in the Biostatistics, Epidemiology, and Research Design (BERD) Center.

By the end of this seminar you will be able to:

  • List the questions you should ask yourself when evaluating a scientific journal article.
  • Identify the specific, testable hypothesis of the paper.
  • Identify what type of study design was used.
  • Evaluate whether the results of the study were affected by bias.
  • Explain why this study was important, what it added to the literature, or how it changed health practice.
  • Appraise the compatibility of the conclusions of the study with the study objectives.

Details

Thursday, April 28th, 2016 1:00 – 2:30PM
Tufts Center for Medical Education, Room 114
145 Harrison Avenue, Boston

Or via live, interactive webcast (a link will be provided to those who register).

 

Seminars & Workshops
Research Database Creation: Basics and Best Practices

Overview

Are you involved in building a database for your research project?

Building an appropriate database for your study is critical to ensuring successful data collection and analysis. Learn how to build a database in this 90-minute Tufts CTSI workshop, Research Database Creation: Basics & Best Practices. This session will begin with an interactive lecture presented by Rachael Huebner, a Clinical Data Manager at Tufts CTSI, followed by a workshop in which participants will practice building a simple database in Excel.

This workshop is a prerequisite to a subsequent workshop, Research Database Creation: Building a REDCap Database.

After attending this event, you should be able to:

  • Recognize database creation best practices
  • Identify the clinical and demographic data needed to answer a study question
  • Effectively name and code variables
  • Create an Excel sheet appropriate for study data collection

Details

Date: Tuesday, October 29, 1:00-2:30PM

Location: Tufts Medical Center, IS Training Room, Ziskind Building, 1st Floor, Room 114A

This workshop is a prerequisite to a subsequent workshop, Research Database Creation: Building a REDCap Database.

Registration

This workshop is designed for research assistants, clinical research coordinators, investigators, residents, and fellows who will be creating or working with databases for research projects.

The workshop is now full. To add your name to the waitlist, please register here.

Tufts CTSI Professional Education & Expectation for Course Participants

Tufts CTSI’s Professional Education programs provide non-degree continuing education and training for clinical and translational research professionals from all Tufts CTSI partners and beyond.

Course enrollment priority is given to researchers from Tufts CTSI partner institutions. If your participation needs to be approved by your supervisor or a person responsible for your time release, you may provide their contact information when you register for the program.

This course is provided free of charge, and was supported by the National Center for Advancing Translational Sciences, National Institutes of health, Award Number UL1TR002544. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

 

Seminars & Workshops
Research Database Creation: Basics and Best Practices 2020

Overview

Are you involved in building a database for your research project?

Building an appropriate database for your study is critical to ensuring successful data collection and analysis. Learn how to build a database in this 90-minute Tufts CTSI workshop, Research Database Creation: Basics & Best Practices. This session will begin with an interactive lecture presented by Rachael Huebner, a Clinical Data Manager at Tufts CTSI, followed by a workshop in which participants will practice building a simple database in Excel.

This workshop is a prerequisite to a subsequent workshop, Research Database Creation: Building a REDCap Database.  Please note, in this workshop, we will not be using REDCap, but we will be learning the fundamentals required for database creation, which will inform our second session where REDCap will be used.

After attending this event, you should be able to:

  • Recognize database creation best practices
  • Identify the clinical and demographic data needed to answer a study question
  • Effectively name and code variables
  • Create an Excel sheet appropriate for study data collection

Details

Date: Thursday, March 12, noon-1:30PM

Location: ONLINE ONLY

This workshop is a prerequisite to a subsequent workshop, Research Database Creation: Building a REDCap Database.

Registration

This workshop is designed for research assistants, clinical research coordinators, investigators, residents, and fellows who will be creating or working with databases for research projects.

To attend, please register here by March 5.

Tufts CTSI Professional Education & Expectation for Course Participants

Tufts CTSI’s Professional Education programs provide non-degree continuing education and training for clinical and translational research professionals from all Tufts CTSI partners and beyond.

Course enrollment priority is given to researchers from Tufts CTSI partner institutions. If your participation needs to be approved by your supervisor or a person responsible for your time release, you may provide their contact information when you register for the program.

This course is provided free of charge, and was supported by the National Center for Advancing Translational Sciences, National Institutes of health, Award Number UL1TR002544. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

 

Seminars & Workshops
Research Database Creation: Building a REDCap Database

Overview

Are you involved in building a REDCap database for your research project?

REDCap is an online application that can be used to create research databases. It has many advantages over Excel, and is often the preferred tool for database creation. Learn how to create REDCap databases for your research projects in this 90-minute Tufts CTSI workshop, Research Database Creation: Building a REDCap Database.

This session will begin with a lecture presented by Rachael Huebner, a Clinical Data Manager at Tufts CTSI, followed by a workshop in which participants will practice building a simple database in REDCap.

To attend this event, participants must attend the first workshop in this series, Research Database Creation: Basics & Best Practices.

After attending this event, you should be able to:

  • Describe the differences between classic and longitudinal projects, and identify when to use each
  • Create projects, forms, and fields in REDCap
  • Export data from REDCap to Excel

Details

Date: Tuesday, November 12, 2:00-3:30PM

Location: Tufts Medical Center, IS Training Room, Ziskind Building, 1st Floor, Room 114A

To attend this event, participants must attend the first workshop in this series, Research Database Creation: Basics & Best Practices.

Registration

This workshop is designed for research assistants, clinical research coordinators, investigators, residents, and fellows who will be creating or working with databases for research projects.

Space is limited. To reserve your seat, please register here by October 24.

Tufts CTSI Professional Education & Expectation for Course Participants

Tufts CTSI’s Professional Education programs provide non-degree continuing education and training for clinical and translational research professionals from all Tufts CTSI partners and beyond.

Course enrollment priority is given to researchers from Tufts CTSI partner institutions. If your participation needs to be approved by your supervisor or a person responsible for your time release, you may provide their contact information when you register for the program.

This course is provided free of charge, and was supported by the National Center for Advancing Translational Sciences, National Institutes of health, Award Number UL1TR002544. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

 

Seminars & Workshops
Research Database Creation: Building a REDCap Database 2020

Overview

Are you involved in building a REDCap database for your research project?

REDCap is an online application that can be used to create research databases. It has many advantages over Excel, and is often the preferred tool for database creation. Learn how to create REDCap databases for your research projects in this 90-minute Tufts CTSI workshop, Research Database Creation: Building a REDCap Database.

This session will consist of a guided tutorial, led by Rachael Huebner, Clinical Data Manager at Tufts CTSI, in which participants will build a simple database in REDCap.

To attend this event, participants must attend the first workshop in this series, Research Database Creation: Basics & Best Practices.

After attending this event, you should be able to:

  • Describe the differences between classic and longitudinal projects, and identify when to use each
  • Create projects, forms, and fields in REDCap
  • Export data from REDCap to Excel

Details

Date: Thursday, March 26, noon-1:30PM

Location: Tufts Center for Medical Education, Room 514 (Computer Lab), 145 Harrison Avenue, Boston

To attend this event, participants must attend the first workshop in this series, Research Database Creation: Basics & Best Practices.

Registration

This workshop is designed for research assistants, clinical research coordinators, investigators, residents, and fellows who will be creating or working with databases for research projects.

Space is limited.

To reserve your seat, please register here by March 19.

Tufts CTSI Professional Education & Expectation for Course Participants

Tufts CTSI’s Professional Education programs provide non-degree continuing education and training for clinical and translational research professionals from all Tufts CTSI partners and beyond.

Course enrollment priority is given to researchers from Tufts CTSI partner institutions. If your participation needs to be approved by your supervisor or a person responsible for your time release, you may provide their contact information when you register for the program.

This course is provided free of charge, and was supported by the National Center for Advancing Translational Sciences, National Institutes of health, Award Number UL1TR002544. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

 

Seminars & Workshops
Research Database Development Part 1: Basics & Best Practices

Overview

Are you involved in building a REDCap database for your research project?

Building an appropriate database for your study is critical to ensuring successful data collection and analysis. Learn how to build your database in this three-part Research Database Development course presented by Tufts CTSI. There are no pre-requisites required for any of the three course registrations, but participation in all three courses is encouraged as they build on each other.

Part 1: Basics & Best Practices

This two-hour session will begin with an interactive lecture presented by Rachael Huebner, MPH, Clinical Data Manager at Tufts CTSI, followed by a workshop in which participants will practice building a simple database in Excel. Participation will be required for the workshop portion.

Pre-requisite: none

Topics covered include:

  • Database development best practices
  • Determining which data to collect
  • Choosing variable types
  • Naming variables
  • Assigning numbers to variables
  • Using Excel to create a database

After attending this session, participants should be able to:

  • Recognize database creation best practices
  • Identify the clinical and demographic data needed to answer a study question
  • Effectively name and code variables
  • Create an Excel sheet appropriate for study data collection

Details

Date: Wednesday, August 26, 10:00AM-noon

Location: online via Zoom

Registration

Members of any Tufts CTSI-affiliated institution are welcome to attend.

To receive the Zoom link, please register here.

Instructors

Rachael Huebner, MPH is the Clinical Data Manager at Tufts CTSI, providing data management support and training to researchers. Prior to joining Tufts, she worked in data management for industry-sponsored clinical trials after receiving her MPH from Boston University School of Public Health.

Tufts CTSI Professional Education & Expectation for Course Participants

Tufts CTSI’s Professional Education programs provide non-degree continuing education and training for clinical and translational research professionals from all Tufts CTSI partners and beyond.

Course enrollment priority is given to researchers from Tufts CTSI partner institutions. If your participation needs to be approved by your supervisor or a person responsible for your time release, you may provide their contact information when you register for the program.

This course is provided free of charge, and was supported by the National Center for Advancing Translational Sciences, National Institutes of health, Award Number UL1TR002544. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

 

Seminars & Workshops
Research Database Development Part 2: Building a REDCap Database

Overview

Are you involved in building a REDCap database for your research project?

Building an appropriate database for your study is critical to ensuring successful data collection and analysis. Learn how to build your database in this three-part Research Database Development course presented by Tufts CTSI. There are no pre-requisites required for any of the three course registrations, but participation in all three courses is encouraged as they build on each other.

Part 2: Building a REDCap Database

This two-hour session will consist of a guided tutorial, followed by a discussion on building REDCap databases for your own research. Participants should be prepared to discuss their research projects. Instructors will work with you to create REDCap accounts prior to this session.

Topics covered include:

  • Introduction to REDCap
  • Creating projects, forms, and fields
  • Exporting data

After attending this session, participants should be able to:

  • Describe the differences between classic and longitudinal projects, and identify when to use each
  • Create projects, forms, and fields in REDCap
  • Export data from REDCap to Excel

Details

Date: Thursday, August 27, 10:00AM-noon

Location: online via Zoom

Registration

Members of any Tufts CTSI-affiliated institution are welcome to attend.

To receive the Zoom link, please register here.

Instructors

Rachael Huebner, MPH is the Clinical Data Manager at Tufts CTSI, providing data management support and training to researchers. Prior to joining Tufts, she worked in data management for industry-sponsored clinical trials after receiving her MPH from Boston University School of Public Health.

Tufts CTSI Professional Education & Expectation for Course Participants

Tufts CTSI’s Professional Education programs provide non-degree continuing education and training for clinical and translational research professionals from all Tufts CTSI partners and beyond.

Course enrollment priority is given to researchers from Tufts CTSI partner institutions. If your participation needs to be approved by your supervisor or a person responsible for your time release, you may provide their contact information when you register for the program.

This course is provided free of charge, and was supported by the National Center for Advancing Translational Sciences, National Institutes of health, Award Number UL1TR002544. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

 

Seminars & Workshops
Research Database Development Part 3: Advanced REDCap Features

Overview

Are you involved in building a REDCap database for your research project?

Building an appropriate database for your study is critical to ensuring successful data collection and analysis. Learn how to build your database in this three-part Research Database Development course presented by Tufts CTSI. There are no pre-requisites required for any of the three course registrations, but participation in all three courses is encouraged as they build on each other.

Part 3: Advanced REDCap Features

This two-hour session will begin with a demonstration of commonly used advanced REDCap features, Informatics Project Coordinator at Tufts CTSI, followed by an interactive conversation answering participants’ real-life REDCap questions.

Topics covered include:

  • Complex piping and calculations within REDCap forms
  • Establishing workflows with the Survey Queue and Alerts and Notifications sections
  • Understanding how Action Tags can be used to help guide data collection
  • Ensuring high-quality input by establishing Data Quality rules

After attending this session, participants should be able to:

  • Identify use cases for advanced REDCap features
  • Implement commonly-used advanced features in REDCap projects

Details

Date: Friday, August 28, 10:00AM-noon

Location: online via Zoom

Registration

Members of any Tufts CTSI-affiliated institution are welcome to attend.

To receive the Zoom link, please register here.

Instructor

Rachael Huebner, MPH is the Clinical Data Manager at Tufts CTSI, providing data management support and training to researchers. Prior to joining Tufts, she worked in data management for industry-sponsored clinical trials after receiving her MPH from Boston University School of Public Health.

Tufts CTSI Professional Education & Expectation for Course Participants

Tufts CTSI’s Professional Education programs provide non-degree continuing education and training for clinical and translational research professionals from all Tufts CTSI partners and beyond.

Course enrollment priority is given to researchers from Tufts CTSI partner institutions. If your participation needs to be approved by your supervisor or a person responsible for your time release, you may provide their contact information when you register for the program.

This course is provided free of charge, and was supported by the National Center for Advancing Translational Sciences, National Institutes of health, Award Number UL1TR002544. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.