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Methodology Honours > week 6 > Flashcards

week 6 Flashcards

1
Q

what is data management?

A

“Data are facts, observations or experiences on which an argument or theory is
constructed or tested.

“Research Data Management covers all of the decisions made during the research
lifecycle to handle research data, from the planning stage of your project up to the
long-term preservation of your data.”

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2
Q

what could data be?

A

Data may be numerical, descriptive, aural or visual. Data may
be raw, abstracted or analysed, experimental or observational.

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3
Q

what includes data?

A

Data include but are
not limited to: laboratory notebooks; field notebooks; primary research data
(including research data in hardcopy or in computer readable form); questionnaires;
audiotapes; videotapes; models; photographs; films; test responses. Research
collections may include slides; artefacts; specimens; samples.”
any notes you take are also data

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4
Q

questions to consider about data management:

A
  • where is your data stored?
  • how will it be analysed?
  • who will have access to the data
  • what are the requirements for sharing data?
  • what quality checks will you conduct?
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5
Q

what do you need when storing data in excel or recap?

A

protect it with secure server, password protection

locked in cabinet for hard copy surveys

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6
Q

what should you include when entering the data?

A

a data dictionary.

define everything, explain everything :)

what they represent, what they are , is it a raw or total score?

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7
Q

how do you code categories when entering data?

A

assingin numerical values e.g. female=0 male=1

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8
Q

what things you should check on the data?

A

if the categories can be collapsed and how accurate the data is.

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9
Q

What should you do with qualitative data?

A

remove identifiable information from file names and documents

have a spreadsheet with identifiable information that is password protected and saved in a different location.

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10
Q

what are three sources of error?

A

data entry mistakes
data omissions
data errors

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11
Q

How could you mitigate errors?

A
  • internal system checks ( if they are permissible values)
  • data integrity checks ( e.g. audit data)
  • third party verification ( e.g compared to admissions data).
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12
Q

should you store your data in a usb?

A

No :)

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13
Q

who will have access to your data?

A

people listed in the ethics application

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14
Q

what are the codes for missing data?

A

some are: 98 for dont know , 99 for refused.

missing reponse : 999 or ‘.’ or blank

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15
Q

what other things should you consider?

A

reporting frequencies
do you include or exclude people with missing data?

what to do with additional reponses ‘other’

reverse coding

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16
Q

what are the 5 approaches to qualitative data analysis?

A 
content ( count words)
discourse
narrative ( find a beginning to an end) 
thematic  (analysis of language, common ideas, global themes)
grounded
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17
Q

what does the approach of the analysis depnds on?

A

research question

theoretical framework

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18
Q

what is thematic analysis

A

(analysis of language, common ideas, global themes)

therems that describe the phenomenon of interest, pattern recognition

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19
Q

what is discourse analysis

A

study of language beyound the sentence.

studies chunks of texts as they flow together. what things mean together.

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20
Q

what should you consider in qual analysis?

A

the influence of you!

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21
Q

is qual analysis objective?

A

no , it is subjective and inductive.

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22
Q

what influences of you should you awknoledge?

A 
 Education
 Gender
 Religious affiliation
 Social class
 Biases, prejudice
 Preconceptions
 Ethnicity
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23
Q

when does qual analysis start?

A 
 Part of the research design
 Part of the literature review
 Part of theory formation
 Part of data collection
 Part of data ordering, filing and reading
 Part of the writing
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24
Q

There are unit of analysis in qual analysis too e.g. :

A 
 A tool to scrutinise your data
 Meanings
 Processes
 Practices
 Encounters
 Narrative structures
 Organisations
 Lifestyles
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25
what sampling does grounded theory use?
theoretical sampling More inductive than thematic analysis
26
what is theoretical analysis?
Theoretical sampling is a process of data collection for generating theory whereby the analyst jointly collects codes and analyses data and decides what data to collect next and where to find them, in order to develop a theory as it emerges.`
27
what are the three main coding procedures?
- open - axial - selective
28
what is open coding?
deconstruction of the transcript. line by line, clustering similar codes, looking for key phrases, topics that re occur, metaphors. concepts first step in coding process applies conceptual labels, groups into categories develop initial relationships , compares
29
what is axial coding?
reconstruction, putting the data back together, interconnecting data.
30
what is selective coding?
deconstructive categories, (core code), categories unified around a core category - think abiut a tree or a buffet with many food.
31
what is the equivalent of a data dictionary in qual aanalysis?
coding guide
32
when the coding guide be developed?
prior to analysis based on lit review, evolves thorugh the process of coding.
33
what are the two types of codes?
FACTUAL (content analysis) or INTERPRETIVE ( thematic analysis/ grounded theory)
34
what is code?
an abbreviation or symbol used to classify | words in the text by categories (themes)
35
what is coding?
process to identify categories of meaning.
36
what is the focus of coding?
Focus is on placing conceptual labels on discrete | happenings, events or other instances
37
what does reflexive thematic analysis focus on?
identify patterns of meaning fata familiarisation data coding theme development
38
what are some types of coding?
``` semantic latent inductive deductive realist constructionist ```
39
what is semantic coding?
explicit content of the data ( factual codes)
40
what is latent coding?
concepts and assumptions underpinning the data
41
what is inductive coding?
derived from the data
42
what is Deductive coding?
existing concepts or ideas
43
what is Realist coding?
reality evident in the data
44
What is constructionist?
how reality is created in the data
45
what are the steps in reflexive thematic analysis?
1. familiarisation with data 2. coding - apply labels to the data. 3. generating initial themes - identify patterns from the coding 4. reviewing themes 5. defining and naming themes 6. writing up
46
can you use both deductive and inductive coding in one project?
yes!
47
what can be coded?
``` Setting and context  Definition of situation  Perspectives  Ways of thinking about people and objects  Process  Activities  Actions  Events  Conditions  Consequences  Strategies  Relationship and social structure  Meanings ```
48
what is clustering?
After open coding an entire text, make a list of all code words and cluster together similar codes.
49
what is clustering objective?
to reduce the long list of codes to a smaller more manageable one. ( 20 to 30)
50
what things should you look for when clustering?
key phrases topics that occur and recur local or commonly used terms used in an unfamiliar way. ( e.g. womens troubles) use of metaphors - what do they represent
51
what are the 9 steps of the codign process according to charmz
- explore general research question - gather data, and code for correspondents meanings - look for relationsihps - coding leads to new categories - collect more data on the devloping categories - go back and read earlier data for the new categories - constantly compare individuals, events... - write memos all the time about categories, processes and ideas. - move towards memos that are more conceptual and codes that are more abstract.
52
steps to verify themes:
1. follow up on surprises 2. traingulate 3. make some if -- then tests 4. check out rival explanations 5. FEEDBACK from informants, experts, colleagues and friends!
53
where can names of themes and categories can come from?
researcher, participant, previous literature
54
what is the most common way to name categories?
when researcher comes up with tems that reflects what he sees in the data.
55
should themes reflect the purpose of the research?
yes
56
what should themes be?
sensitizing - sensitive to what is in the data. conceptually congruent -- same level of abstraction.
57
what are the types of themes?
ordinary unexpected hard-to-classify major and minor
58
what is ordinary theme?
a theme a researcher expects
59
what are hard to classify themes?
themes that contain ideas that do not easily fit into one theme or that overlap with several themes
60
what are the typical challenges ?
drowning in data hearsay include the 'so what' factor?
61
how to include a so what ( point, moral or purpose) factor?
Tip: Answer one of the following questions somewhere in your story: 1. What did your character(s) learn? 2. How did your character(s) change? 3. How did your character(s) mature? 4. Why were the events of the story meaningful or important to your character(s)? 5. What should your readers learn? 6. What do the events in your story tell us about people / human nature?
62
what is theoretical framework?
e.g (e.g. Stages of brief, are they in stage of acceptance?)
63
what is a research personality statement?
when you do qualitative analysis and need to inform your background for people to be aware of your potential bias.

Methodology Honours (8 decks)

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