CYSTINET - Africa Consortium

STATISTICAL DATA ANALYSIS TRAINING WORKSHOP

WORKSHOP DURATION: 21-25 JUNE, 2021

VENUE:  Centre for Educational Development in Health Arusha (CEDHA), Arusha, Tanzania.

1.0 BACKGROUND

As big data becomes the norm and experiments continue to increase in scale, proper understanding and use of statistics are becoming increasingly important for scientists in every field, especially in this era of evidence-based research, where authors must endeavor to produce high-level evidence articles. Peer reviewers and editors reported that 71% of the manuscript deficiencies that most frequently led to rejection were related to weak statistical analysis and poor methodological descriptions, (Byrne,2000). Appropriate application of statistical principles and tools in the methodology and results sections of a manuscript increases the probability of acceptance of the manuscript.

While experimental researchers are expert in concepts related to their respective fields and receive extensive scientific education, statistical training is relatively lacking or weak. Unfortunately, this knowledge gap can result in both reduced understanding of reported results in scientific publications as well as potentially inaccurate reported statistics.

To close the knowledge gap and help  early career researchers learn how to choose a statistical test for their data, how to perform those tests, and how to interpret the results, CYSTINET-Africa project at SUA in collaboration with NIMR is organizing  a workshop to advance data analysis skills and consequently improve the quality of manuscripts by involving expert methodologists (biostatisticians/ statisticians, and epidemiologists) who will share their experience to improve the quality of your research outputs to be published in high profile journals. Main goal is to enhance the biostatistics/statistical skills of researchers and professionals involved in the analysis of data.

A key focus is on providing practical skills which will assist the participants to learn how to correctly choose a statistical test, perform those tests, to quantify their experimental results and how to properly interpret the results of those statistical tests, based on real data already collected in the recent projects.

2.0 Training contents

The workshop will start by establishing a solid foundation in basic epidemiological and statistical theory before advancing to practical applications of statistical tests on real data already collected in the recent projects. The emphasis will be on data cleaning, analysis, interpretation and concepts rather than calculations or mathematical details.

An overview of some methods in survival analysis will be covered. Concepts of study design including randomization, and application of statistical models. A focus will be on using data sets from actual clinical and epidemiological studies to illustrate the introduced statistical methods and show how to make scientific interpretations from the numerical results. Statistical inference from data derived from multivariable regression models, including linear, logistic, Poisson and Cox regression models,as well as  impact evaluation models.

Concepts applying a variety of analytic techniques with statistical software such as SAS/R/SPSS and STATA will be used. Students can also choose a software based on their own preference when doing exercises. The presentation emphasizes interpretation of the methods rather than technical details, with examples including randomized clinical trials and social survey data.

These will be preceded by a brief presentation on basic concepts used in statistical inference including hypothesis testing, p-values, odds ratio, confidence intervals, t-test and ANOVA.

Participants will learn basic methods of data organization/management and simple methods for data exploration, data editing, graphical and tabular displays and data presentation.

3.0 Learning Objectives

Upon completion of the workshop, participants will have the confidence, knowledge, and resources to:

1. Understand basic theories underlying many popular statistical tests
2. Understand recent advances in statistical issues: recent models applied in biomedical/statistical data, clinical and public health research
3. Determine the appropriate statistical test to use given a data-set and a research questions
4. Perform basic statistical tests, Interpret and understand output from statistical tests

4.0 Who should attend?

The statistical data analysis workshop is targeted to CYSTINET-Africa PhD and Master students at NIMR and SUA. The students’ supervisors in Tanzania are invited to attend and share their experience. Any post-graduate clinical and public health researchers and investigators who have original research data intended for analysis support and publication are eligible to apply.  A maximum of 35 researchers and postgraduate students will be selected and notified on 18^th June,2021. Participants are strongly encouraged to attend all workshop sessions for active engagement in discussion. Selected participants will benefit from intensive, interactive hands-on training during which they will develop their own analyses and manuscripts with the goal of submitting to a journal for publication.

5.0 Training Facilitators

Workshop training facilitators shall be selected from experienced SUA researchers /statisticians/epidemiologists and Journal editors in collaboration with biostatisticians from Kilimanjaro Christian Medical University College (KCMUCo), MUHAS and University of Dar es Salaam (UDSM).

6.0 Mode of delivery

The training workshop shall be delivered through interactive lectures, group and individual works and hands-on practice.

7.0 Participation fee

No fee for attending the course. Per diems, accommodation and travel costs will not be covered. Training materials will be provided but participants will bring their own laptops. Participants will be provided with the certificates of attendance.

8.0 How to apply

Interested applicants shall send an application letter/email explaining his/her motivation to attend the workshop, an abstract indicating:

1. Research title
2. Problem statement
3. Objectives
4. Methods especially data collection methods
5. Data analysis plan

Deadline for receiving applications will be on the 14th June, 2021. Only selected candidates shall be contacted.

Please fill in the application form