# MATH07040 2020 Advanced Statistical Methods for Health Research

### General Details

Full Title
Advanced Statistical Methods for Health Research
Transcript Title
Code
MATH07040
Attendance
N/A %
Subject Area
MATH - Mathematics
Department
HEAL - Health & Nutritional Sciences
Level
07 - NFQ Level 7
Credit
10 - 10 Credits
Duration
Semester
Fee
Start Term
2020 - Full Academic Year 2020-21
End Term
9999 - The End of Time
Author(s)
Programme Membership
SG_SINFO_B07 202000 Bachelor of Science in Health and Medical Information Science SG_SDATA_E07 202000 Certificate in Health Data Analytics
Description

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.

### Learning Outcomes

On completion of this module the learner will/should be able to;

1.

Demonstrate the application of advanced statistical techniques in the analysis of population health data.

2.

Describe the selection and application of appropriate quantitative analysis in global health literature and reports.

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

### 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.

### Repeat Assessments

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.

### Indicative Syllabus

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

Coursework & Continuous Assessment
50 %
End of Semester / Year Formal Exam
50 %

### Coursework Assessment

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

Type Location Description Hours Frequency Avg 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
Total Online Learning Average Weekly Learner Contact Time 4.00 Hours

### 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.