Summary lectures + aim Research Methods in Health Sciences
Summary lectures exam 2 Research Methods for Analyzing Complex Problems (AM_1182)
Summary lectures exam 1 Research Methods for Analyzing Complex Problems (AM_1182)
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Vrije Universiteit Amsterdam (VU)
Master MPA
Research Methods for Analyzing Complex Problems (AM_1182)
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Doing research in the real world - Gray & Jensen (2022)
Chapter 27: Analysing and presenting qualitative data
Qualitative analysis = a rigorous and logical process through which data are given meaning.
→ elements:
- Analytic induction = if a single case is inconsistent with the hypothesis, then either
further data have to be collected, or the hypothesis has to be reformulated.
- Steps in coding process: transcribe data -> collect/code/collect -> familiarisation ->
focused reading -> review/modify codes -> generating theory.
- Secondary data analysis = analysis of another researcher’s qualitative data/documents.
- Reflexivity = relationship between the researcher and the object of research →
realisation that the researcher is not a neutral observer.
→ 2 forms: (1) epistemological (researchers reflect on their assumptions about the world and
about the nature of knowledge), and (2) personal (researchers reflect upon how their personal
values, attitudes, beliefs and aims have shaped the research).
→ achieving reflexivity: (a) involving multiple investigators, (b) writing a reflexive journal, (c)
reporting research perspectives, values and beliefs in any research report.
→ dangers to reflexivity: narcisim, self-righteousness, nihilism (too conscious of the constraints
on research), and arrogance.
Types of analysis:
- Content analysis = making inferences about data (usually text) by systematically and
objectively identifying special characteristics (classes or categories) within them →
creating criteria of selection.
→ criticism: lead to the fragmentation and decontextualization of data away from the social
processes they are meant to represent.
- Thematic analysis = identifying and analysing patterns (themes) within qualitative data
→ inductive (themes emerge from the data themselves) vs. theoretical (emerges from the
researcher’s theoretical stance).
- Grounded theory = theory is discovered, developed and provisionally verified through
systematic data collection and analysis of data pertaining to that phenomenon.
→ open coding: disaggregation of the data into units → naming and categorizing phenomena.
→ axial coding: recognizing relationships between categories identified through open coding →
identifying (a) a category (phenomenon) and what causes it, (b) the context in which it arises, (c)
the actions and interactions that stem from it, (d) its consequences.
→ selective coding: the integration of categories to produce a theory → selecting core categories
from the data to form the grounded theory.
- Narrative analysis = capturing the lived experiences of participants.
- Conversational analysis = formal analysis of everyday conversations (natural texts).
- Discourse analysis = how spoken and written language are used in social contexts →
focus on structure and organization of language with an emphasis on how participants’
versions of events are constructed.
Validity = whether a researcher is observing, identifying or measuring what they claim they are.
→ external validity: degree to which findings can be generalised to other settings.
→ internal validity: whether there is compelling evidence that the researcher has achieved a
strong link between their evidence and the theoretical ideas they develop from it.
Reliability = external reliability: extent to which the findings of a study can be replicated →
internal reliability: use of more than one observer/interpreter in the field.
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