Module 21-23 - Refinement Flashcards
Qualitative Data types - Discrete vs Continuous variables
Continuous variable: measurement can be refined depending upon the precision of your measurement instrument. Height of penguin, 3.756feet
Discrete: measurement cannot be broken down into fractions. You cannot count 3 and ½ penguins
Qualitative Data types - Classifying of Variables: Discrete or Continuous?
-Height
- Religion
- Blood pressure
- VO2max
- Number of children in a
family
- Number of times you use
your phone per day
- Number of minutes you use
your phone per day
-Height, continuous
- Religion, discrete
- Blood pressure, continuous
- VO2max, continuous
- Number of children in a
family, discrete - Number of times you use
your phone per day, discrete - Number of minutes you use
your phone per day, continuous
Qualitative Data types - Variables: scales of measurement
- Nominal scale (1)
Nominal scale - scale in which objects or individuals are assigned to categories that have no numerical properties
* Categories according to a criterion
* Discrete variable
Qualitative Data types - Variables: scales of measurement
- Ordinal Scale (2)
A scale in which objects or individuals are categorized and the categories form a rank
* Discrete variable
* Pain Measurement scale
- distance between values does matter ( just order)
Qualitative Data types - Variables: scales of measurement
- Interval scale (3)
Units of measurement, intervals between the numbers on scale are equal in size BUT there is no absolute zero
* Has direction and magnitude, and equal distance between values
* Continuous variable
Qualitative Data types - Variables: scales of measurement
- Ratio scale (4)
A scale that has magnitude,
direction, and equal units of
measurement.
* There is an absolute zero that
indicates an absence of the
variable
* Continuous variable
Qualitative Data types - Scale of measurement
- Highway #1?
- Race time of 18:30?
- 27th in line of 3000?
- A team of 4 women in golf league?
- Average temp is 20o C?
- Money?
- 25 out of 25 correct?
- Finishing 3rd in a race?
- Highway #1?
- Nominal, discrete - Race time of 18:30?
- Ratio, continuous - 27th in line of 3000?
- Ordinal, discrete - A team of 4 women in golf league?
- Nominal, discrete - Average temp is 20o C?
- Interval, continuous - Money?
- Ratio, continuous - 25 out of 25 correct?
- Ratio, continuous - Finishing 3rd in a race?
- Ordinal, discrete
Qualitative data generation - Qualitative strategies of inquiry
- Philosophical views of the research
- Sampling / access
- Methods (data generation and data analysis)
- Qualitative = continuous
Qualitative data generation - Qualitative research…
Researchers are key instruments
Use of the term “data generation” rather than “data collection”
- Emphasizes the way researchers and participants work together to generate
data
- Research occurs in the natural setting
- Qualitative research is emergent
Qualitative data generation -
Narrative
- Stories are used to bring understanding or meaning to the lived experiences of individuals
- Stories typically generated via in-depth and unstructured interviews
Qualitative data generation -
Ethnographies
- Driven by questions that seek to understand cultures or a cultural group
- Participant observation is typically the primary process used for data generation
Qualitative data generation -
Phenomenology
- The study of a phenomenon or a concept through the exploration of lived experiences
- Data is typically generated via multiple in-depth interviews with participants
Qualitative data generation -
Case study
Complexity and distinctiveness of a case within important circumstances
- The case or “bounded system” is bound by time and place
Qualitative data generation -
Grounded theory
- Focused on the generation and analysis of data to construct a theory
- The “End product” is a theory
- Data typically generated via one-on-one interviews with participants
Purposeful sampling
To recruit a sample of information-rich participants who will purposefully inform an understanding of the topic being studied
- Extreme case sampling
- Maximum variation sampling
- Snowball sampling
Saturation
Saturation is the idea that enough data has been obtained and that more data will not improve understanding. See below for determining saturation
Interviews
Interviews are the most common method for generating data in qualitative research
Qualitative studies often use more than one method of data generation
- One-on-one interviews
-Group interviews - Important to build rapport
Types: Structured, Semi-structured, unstructured
Phases: Intro, questioning, closing
Qualitative data analysis - Phineas Gage
Phineas Gage 1823-1860
- In an accident a tamping rod shot through his head
damaging much of his left pre-frontal lobe - Although he survived the injury his personality was
dramatically changed, and friends and family no longer
saw him as the person who he was before the accident - First reported case of the effects of pre-frontal lobe
damage on personality
Qualitative data analysis - Subjective, does fit into numbers
- Emotions
- Feelings
- Perceptions
- Beliefs
-Motivations - Barriers
Qualitative data analysis - Objective
- Behaviours
- Social interactions
- Cultural norms
- Experiences
- cognitive responses
- Quality of life
Qualitative data analysis - Goal of qualitive analysis
Create a taxonomy: a formal system for classifying multi-faceted and complex phenomenon
oDevelop themes: a way to characterize the responses of
participants and provide insight into experiences
oDevelop theory: a set of interlocking causal variables to explain realities
- Need goal of research
Qualitative data analysis - what kind of process
- immediate, ongoing, spiral process
Qualitative data analysis - steps in qualitative analysis
Step 1: Organize and prepare the data
oStep 2: Read or look at all the data
oStep 3: Start coding all the data
oStep 4: Generate descriptions or themes
oStep 5: Decide how the findings will be represented
oStep 6: Interpret the findings
