MATH07040 2020 Advanced Statistical Methods for Health Research
This module will equip the student with advanced statistical techniques for analysing health related data. It provides the students with the ability to apply appropriate advanced statistical techniques to data sets gathered during project work and to publicly available health related datasets. Students will also evaluate statistical analysis approaches used in existing research studies and comment on their appropriateness.
On completion of this module the learner will/should be able to;
Demonstrate the application of advanced statistical techniques in the analysis of population health data.
Describe the selection and application of appropriate quantitative analysis in global health literature and reports.
Identify key features of quantitative analysis including descriptive and inferential statistics in a range of study designs
Evaluate the appropriateness of statistical approaches in a range of health settings.
Perform advanced statistical analysis on health data using SPSS
Teaching and Learning Strategies
This module will be delivered using a combination of theory based online lectures, online computer based workshops and self-study. The student's learning will be supported by a range of supplemental content available on the module page in the institutes' VLE (Moodle). This supplemental content will include notes, practical manuals and videos.
The principles of UDL will underpin the design of all module content to ensure maximum accessibility for all learners.
Module Assessment Strategies
he student will be assessed by means of both summative and formative assessment. The summative assessment will consist of a practical based continuous assessment and a project where the student will be examined on both their theoretical knowledge of statistics and their use of statistical analysis software to apply this knowledge with the emphasis on the practical application of statistics. They will also take an end of module exam which will concentrate on their theoretical knowledge.
The student will also have access to online self-assessment quizzes as part of the formative assessment. These quizzes will allow the student to monitor their own progress on the module as well as identify any knowledge gaps they may have.
Where the student fails to achieve the pass mark in the module, they may be asked to repeat the final exam or complete a practical assignment or a combination of both.
1. Demonstrate the application of advanced statistical techniques in the analysis of population health data.
- Standardisation of Death/Birth Rates (both Direct and Indirect)
- Incidence Rates/Prevalence
- Odds Ratio/Relative Risk/2 x 2 Tables and Chi-Square tests
- Hazard Ratios
2. Describe the selection and application of appropriate quantitative analysis in global health literature and reports
- Identification of statistical methods used in Research
- Critical Appraisal of Statistical Methods in research
3. Identify key features of quantitative analysis including descriptive and inferential statistics in a range of study designs
4. Evaluate the appropriateness of statistical approaches in a range of health settings.
5. Perform advanced statistical analysis on health data using SPSS.
- Sample Size Calculations/Effect Size/Power
- One Sample, Independent Samples and Paired Samples t-tests
- One-Way ANOVA and related Post Hoc Tests
- Repeated Measures ANOVA and related Post Hoc Tests
- Two Way ANOVA and related Post Hoc Tests
- z-tests for proportion size
- Non Parametric Tests
- Introduction to Non-Parametric hypothesis tests
- Chi-Square test for association and Independence
- Mann-Whitney test
- Kruskal Wallis test
- Wilcoxon signed-rank test
- Relationship Modelling
- Pearson's Correlation Co-efficient
- Significance of the correlation co-efficient
- Spearman's Rho
- Simple Linear Regression/Multiple Regression analysis
- Reliability Analysis
- Advanced Charts for Public Health and Epidemiology (Forest Plots etc.)
- Time to Event Analysis/Survival Analysis
- Factor Analysis
Coursework & Assessment Breakdown
|Title||Type||Form||Percent||Week||Learning Outcomes Assessed|
|1||Statistical Analysis - Practical Evaluation||Practical||Practical Evaluation||20 %||Week 7||1,3,5|
|2||Statistical Analysis Project||Project||Assignment||30 %||Week 13||1,2,4,5|
End of Semester / Year Assessment
|Title||Type||Form||Percent||Week||Learning Outcomes Assessed|
|1||Final Exam||Final Exam||Closed Book Exam||50 %||End of Term||1,2,3,4|
Online Learning Mode Workload
|Online Lecture||Distance Learning Suite||Online Lecture||2||Weekly||2.00|
|Workshop||Distance Learning Suite||Online Computer Based Workshop||2||Weekly||2.00|
|Independent Learning||Offsite||Student Self Study||4||Weekly||4.00|
Required & Recommended Book List
2011-08-17 Biostatistics: An Applied Introduction for the Public Health Practitioner Cengage Learning
ISBN 9781133708957 ISBN-13 1133708951
BIOSTATISTICS: AN APPLIED INTRODUCTION FOR THE PUBLIC HEALTH PRACTITIONER is designed to help public health researchers, practitioners, and students understand and apply essential biostatistics concepts. This innovative new text emphasizes real-world public health problems and the research questions they inspire. This text provides a unique introduction to statistical concepts and methods used by working professionals during investigations. Unlike other texts that assume a strong knowledge of mathematics or rely heavily on formulas, BIOSTATISTICS consistently emphasizes the public health context, making even complex material both accessible and relevant. The first chapter introduces common statistical terminology by explaining them in clear language, while subsequent chapters explore the most useful and versatile statistical methods for a variety of public health research questions. For each type of question, the author presents a range of applicable methods, from descriptions of data to simple statistical tests, generalized linear models, and multiple variable regression. The text's step-by-step coverage of fundamental concepts is perfect for students new to the field, but its depth and detail also make it ideal for two-course series in M.P.H. or M.H.A. programs, or for working professionals. Readers at all stages of their professional lives can draw on this invaluable resource to help them interpret and conduct statistical studies and support effective evidence-based practice. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
2017-02-17 Essentials of Biostatistics in Public Health Jones & Bartlett Learning
ISBN 9781284108194 ISBN-13 1284108198
Study designs -- Quantifying the extent of disease -- Summarizing data collected in the sample -- The role of probability -- Confidence interval estimates -- Hypothesis testing procedures -- Power and sample size determination -- Multivariable methods -- Nonparametric tests -- Survival analysis -- Data visualization
2018-11-13 Biostatistics Wiley
ISBN 9781119282372 ISBN-13 1119282373
The ability to analyze and interpret enormous amounts of data has become a prerequisite for success in allied healthcare and the health sciences. Now in its 11th edition, Biostatistics: A Foundation for Analysis in the Health Sciences continues to offer in-depth guidance toward biostatistical concepts, techniques, and practical applications in the modern healthcare setting. Comprehensive in scope yet detailed in coverage, this text helps students understandand appropriately useprobability distributions, sampling distributions, estimation, hypothesis testing, variance analysis, regression, correlation analysis, and other statistical tools fundamental to the science and practice of medicine. Clearly-defined pedagogical tools help students stay up-to-date on new material, and an emphasis on statistical software allows faster, more accurate calculation while putting the focus on the underlying concepts rather than the math. Students develop highly relevant skills in inferential and differential statistical techniques, equipping them with the ability to organize, summarize, and interpret large bodies of data. Suitable for both graduate and advanced undergraduate coursework, this text retains the rigor required for use as a professional reference.