Table of Contents
1. Week 1 Background
2. Week 2 Assessing Research ... ... ...2
3. Week 3 Experimental Methods I . ... 4
3 Week 4 Experimental Methods II ... . . . 6
4 Week 5 Survey Methods . ... 7
5 Week 6 Ethics . . ...10
6 Week 7 Research with Special Populations ... ... 12
7 Week 8 Qualitative and Mixed Methods . ... 14
10 Week 10 Observational Research . ... 17
11 Week 11 Using Existing Datasets . ... 20
12 Week 12 Comparing Research Strategies . ... 22 13 Week 13 Internet Research ...
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Wk8 Qualitative and Mixed Methods
Qualitative research
Research questions rather than hypotheses Examining TYPES of events & interactions
Exploratory: when unsure what to measure; new area of research
- E.g. background for scale development A researcher wants to develop a measure
- E.g. Qualitative question: What is self-esteem?
To capture phenomenology Exploring cultural differences
Sources of qualitative data
Case studies (e.g. clinical work)
- Understand a case in depth
- Generalisability?
- Extreme case sampling (i.e. rare cases)
- Brain damage, rare disorders
- Difficult to get sample size larger than 2 or 3 people Interviews
- Structured
Interview protocol
Instructions & questions to be asked
- Semi-structured
Probes: sub-questions used to gain further information Allows clarification & elaboration
- Idiographic approach
Interested in individual rather than group
Focus groups
Naturalistic observation (e.g. types of interactions b/w parents & children)
- Real world
- Affect of observer?
- Inferences?
Public documents e.g. media items Online forums, blogs
Content and thematic analysis
Systematic categorisation of data
- Data: words, phrases, sentences, paragraphs Coding variables that emerge in the data
- Open coding: the process of selecting & naming categories from the analysis of the data
- Axial coding: Identifying themes (patterns) within the data Attempting to plot the interactions between these variables Bottom up vs. top down approach
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Grounded theory
- Analysis of the data without preconceived hypothesis
- Examining the relationships b/w concepts
- Generating theory from the data
- Data saturation: Gathering data until no new information
- Generating Thematic maps Software for qualitative analysis
- Help arrange and sort data
- E.g. NVIVO
Reporting qualitative research
Similar in layout and structure to quantitative and stuff
Advantages
Rich description of data Need fewer Participants
Disadvantages
Coding/categorising: more difficult than statistical analysis Very time-consuming
Subjectivity? Biases?
- Increasing objectivity:
Blind raters (i.e. double-blind) inter-rater comparison
Mixed-methods approach
Mixed-methods approaches
Both quantitative & qualitative analyses Triangulation:
- Using more than one method to study the same research question
- Combination of qualitative & quantitative methods Why use mixed-methods
- Complementarity
Develop deeper understanding of a research problem
- Development
Results from one study help develop or inform the other method
- Initiation
Clarifying contradictions in findings
- Expansion
To extend the breadth and range of a study Examples:
- QUAL/QUANT Complementarity
Comparing/contrasting qualitative & quantitative findings
E.g. Quantitative likert phone survey and Qualitative semi-structured interview
- qual/QUANT Development
16 E.g. exploratory qualitative study used as a basis for major quantitative study
- quant/QUAL Development
E.g. quantitative screen study used to identify Ss for large-scale qualitative study
- QUANT/qual Initiation
Primary quantitative study first with secondary follow-up qualitative study E.g. exploring aspects of a quantitative study with qualitative research
- QUAL/quant Expansion
Primary qualitative study first with secondary follow-up quantitative study E.g. testing whether qualitative findings transfer to other populations
