Handbook home
Data Analysis in Clinical Research (CLRS90010)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
October
School of Melbourne Custom Programs
Currently enrolled students:
- General information:http://go.unimelb.edu.au/22wa
- Email:TL-ClinicalResearch@unimelb.edu.au
Future students:
- Further information:http://go.unimelb.edu.au/22wa
- Email:TL-ClinicalResearch@unimelb.edu.au
Overview
Availability | October |
---|---|
Fees | Look up fees |
Data analysis methods are an integral part of modern clinical research. They are powerful techniques that enable researchers to draw meaningful conclusions from data collected through observation, survey, or experimentation.
However, data analysis is a huge discipline with different paradigms, schools of thought and alternative methodologies. Therefore consideration of the appropriate methods used must be undertaken when designing a study and selecting variables and groups.
This subject introduces students to the basic principles of qualitative and quantitative data analysis techniques. It will provide a functional grounding in the theoretical concepts behind each type of analysis, as well as exploration of the interpretation of data and the difference, where applicable, between clinical vs statistical significance.
Analysis techniques to be explored include:
Quantitative
- Descriptive statistics
- Principles of statistical inference
- Cross-tabulations: Chi-Square, Fisher’s exact test, relative risk, and odds ratios
- Comparisons of means: t-tests and ANOVA
- Linear association: correlation and simple regression
- Measurement of exposure
- Sample size and power
- Data storage, management, collation and coding
- Quantitative analysis software
Qualitative
- Documentation of data and the process of data collection
- Data transcription
- Effective data storage and management
- Requirements of data coding
- Iterative, content/thematic, narrative, discourse, framework and grounded theory analysis
- Writing up qualitative research
- Qualitative analysis software
Intended learning outcomes
On completion of this subject students should be able to:
- describe the theoretical concepts behind a range of qualitative and quantitative data analysis techniques
- compare and contrast the strengths and weaknesses of different qualitative and quantitative data analysis techniques
- describe a strategy for selecting an appropriate data analysis technique based on the study design selected and/or research data collected
- competently perform a range of basic data analysis techniques using appropriate analysis software and interpret analysis output/s
- provide a rationale for the importance of statistical power and perform power calculations
- identify and discuss the key elements associated with ensuring data integrity including storage, management, collation and coding
- critically compare and contrast statistical vs clinical significance and its relevance to clinical practice
- demonstrate confidence in discussing the validity of data analysis outcomes reported in the scientific literature.
Generic skills
- to engage with unfamiliar problems and identify relevant data analysis strategies
- to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of data analysis
- communicate advanced data analysis concepts in written and oral form;
- the ability to comprehend complex data analysis information
- exercise responsibility for their own learning;
- manage their time effectively.
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
Students must complete CLRS90011 Study Design in Clinical Research and CLRS90027 Principles of Clinical Research prior to enrolment in this subject.
Code | Name | Teaching period | Credit Points |
---|---|---|---|
CLRS90027 | Principles of Clinical Research | March (On Campus - Parkville) |
12.5 |
CLRS90011 | Study Design in Clinical Research | May (On Campus - Parkville) |
12.5 |
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
Participants must demonstrate an elementary understanding of statistics. To achieve this, they will be required to complete an online module prior to commencement of the intensive teaching period (see assessment for requirements).
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 3 November 2022
Assessment
Additional details
- Hurdle Requirement - formative examination: To confirm a baseline understanding of statistics, all participants will be required to complete an online module followed by a formative examination. This will consist of a mixture of MCQ and extended match questions. The pass mark will be set at 80 but participants may complete the assessment repeatedly to achieve this hurdle. The examination is not timed but it must be completed prior to the commencement of the intensive teaching period. Participants will be unable to join the intensive teaching period until this task is successfully completed.
- In-class report describing the rationale/justification/results of the analysis of a variety of different types of research data (equivalent to 2000 words). The report due at the completion of the intensive teaching period (50%).
- 1 x 90 min examination (equivalent to 1500 words) on the last day of the intensive teaching period (30%).
- Critical discussion of the data analysis techniques reported in a clinical research study selected by negotiation with the Subject Co-ordinators (equivalent to 1000 words) due 2 weeks after the intensive teaching period (20%).
Last updated: 3 November 2022
Dates & times
- October
Principal coordinator Charles Malpas Mode of delivery On Campus (Parkville) Contact hours 40 hours (5 day intensive block) Total time commitment 170 hours Teaching period 23 October 2017 to 27 October 2017 Last self-enrol date 24 October 2017 Census date 3 November 2017 Last date to withdraw without fail 10 November 2017 Assessment period ends 17 November 2017 October contact information
School of Melbourne Custom Programs
Currently enrolled students:
- General information:http://go.unimelb.edu.au/22wa
- Email:TL-ClinicalResearch@unimelb.edu.au
Future students:
- Further information:http://go.unimelb.edu.au/22wa
- Email:TL-ClinicalResearch@unimelb.edu.au
Time commitment details
170 hours
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Graduate Certificate in Clinical Research Course Graduate Diploma in Clinical Research Course Master of Clinical Research Course Professional Certificate in Clinical Research - Links to additional information
Last updated: 3 November 2022