1. Linking analysis methods
MEDI6302
Session 3
Linking analysis methods
to research questions
Sydney
Broome
Fremantle

2. question, design & analysis are linked
Research
question, design & analysis are linked
Analysis method
Research question
Research design
© Eric J. Visser 2017 UNDA. All rights reserved

3. Analysis method Determined by the research question & design
Organises & presents data in systematic & understandable way
Tests data to answer research questions (hypotheses)
Described in methods section of paper
Data analysis is presented in results section
Three main research analysis methods are …
© Eric J. Visser 2017 UNDA. All rights reserved

4. Analysis method Qualitative -describes & interprets data Quantitative
-e.g. case reports, interviews, diaries
Quantitative
-organises, tests & presents data mathematically
-statistical approach
-basis of hypothesis testing
Mixed-methods
-combination of qualitative & quantitative methods
© Eric J. Visser 2017 UNDA. All rights reserved

5. Qualitative analysis
Describes & interprets data to identify meanings & patterns, without using mathematical analysis
Popular in social sciences
No hypothesis testing involved
Data gathering: observations, interviews, questionnaires, documents
Analysis methods: phenomenology, ethnography, grounded theory
Presentation: text, tables, diagrams
Qualitative research may lead to confirmatory quantitative studies

6. Qualitative
methods
Phenomenology: in-depth interviews to describe how individuals experience a phenomenon
Ethnography: rich & holistic description of the culture of group under study
Grounded theory: development of a “bottom-up” theory based on data analysis, often collected by in–depth interviews
Case study: detailed accounts of one or more cases

7. Learning task 1 Qualitative methods
Provide an example of how qualitative research might be used to investigate a medical condition affecting a remote aboriginal community in WA?
Provide a historical example of how qualitative research was used to investigate a 19th century health-care problem?
© Eric J. Visser 2017 UNDA. All rights reserved

8. Quantitative methods Descriptive statistics
-organises & presents data in ‘digestible’ form
-e.g. frequency, central tendency, spread
-presented in tabular or graphical form
Comparative statistics (probability TESTING: significance, effect size)
-differences between groups (e.g. t-test, Chi square, ANOVA)
-associations between groups (e.g. correlation, regression)
-effect-size (e.g. NNT, Forest plots)
-basis of hypothesis testing

9. Descriptive statistical analysis
Learning task 2
Descriptive statistical analysis
Understand the role of descriptive statistics in data analysis
How are descriptive statistical data presented in a paper?
How is the central tendency & spread of data analysed?
Draw & understand key features of a normal distribution
Understand interquartile range & ‘box-and-whisker plot’
© Eric J. Visser 2017 UNDA. All rights reserved

10. Statistical power & sample size
Probability of rejecting Null hypothesis when H1 is TRUE
Reduces risk of a false negative result (type II error)
Determines sample size
Power calculation is always required in quantitative research
Can be performed before or after a study is completed
Must be reported as part of trial design
Informs the research design, logistics, timeline, viability
Consult a statistician EARLY about power analysis
© Eric J. Visser 2017 UNDA. All rights reserved

11. Power
Analysis
© Eric J. Visser 2017 UNDA. All rights reserved

12. Learning task 2 Statistical power & sample size
Define type I & type II error
What is the β-risk?
What is the α-risk?
What is the meaning of 1-β?
What three factors affect statistical power?
How will you report power analysis in your paper?
Calculate the sample size required for your research

13. End
© Eric J. Visser 2017 UNDA. All rights reserved

14. Descriptive statistical analysis Data presented as: Tables Histograms
Distribution curves
Box-and-whisker plots
© Eric J. Visser 2017 UNDA. All rights reserved

15. Distribution curve Frequency or Probability Outcome
© Eric J. Visser 2017 UNDA. All rights reserved

16. Distribution curve derived
from histogram
© Eric J. Visser 2017 UNDA. All rights reserved

17. Normal
distribution
Continuous probability curve of frequency of an outcome
© Eric J. Visser 2017 UNDA. All rights reserved