RM and stats Flashcards
What does the difference between the means of 2 groups depend on?
- means, s.ds, var. and pop.
sample
What is Cohen’s D?
A measure of distance between 2 condition means which takes variability into account
How do you calculate Cohen’s D?
(m1 - m2) / meanSD
meanSD = (s1 + s2) / 2
can do same use pop. meand and s.d
for Cohen’s D:
as overlap decreases, does effect size increase or decrease?
increases
Give an example of a small, medium and large effect size
0.2, 0.5, 0.8
What are the two types of 2 sample t-tests? When are they used?
- related (paired, repeated measures) t-test - use when ppts take part in both conditions of ppt design
- independent t-test - use when ppts perform only 1 of 2 conditions between ppt design
How to calculate a related t-test for a 1 tail hypothesis?
- calculate the mean change between the 2 conditions (post - pre)
- calculate change s.d. change between 2 conditions
- assuming null is correct means pop. m = 0
- calculate ese.
- calculate t statistic and use to find p
How to calculate a related t-test for 2 tailed hypothesis?
same method as when calculating for 1 tailed but making sure to find p relating to two-tailed rather than one
What is the mean for a sampling distribution of difference?
pop. mean A - pop. mean B (= pop. mean D)
= 0 if assuming null is true
What is the s.d. for a sampling distribution of difference?
SQRT(pop. s.d. A^2/nA + pop. s.d. B^2/nB)
How do you calculate a z-score for an independent t-test?
Is this used often? Why?
z = (mA-mB) - (pop. meanA-pop. meanB) / SQRT(pop. s.d. A^2/nA +pop. s.d. B^2/nB) ~ N(0, 1)
not often used as often don’t have access to pop. s.d.
How do you calculate a t-statistic for an independent t-test?
t = (mA-mB) - (pop. meanA-pop. meanB) / SQRT(sA^2/nA + sB^2/nB)
v = nA + nB - 2
What is another way of writing SQRT(sA^2/nA + sB^2/nB)?
SQRT(e.s.e. A^2 + e.s.e. B^2)
What is covariance?
The extent to which a change in one variable is associated with predictable change in another variable
What would high and low covariance suggest?
high covariance = if scores for one variable change than the scores for the other variable also change is a predictable manner
low covariance = changes in 1 variable aren’t accompanied by a predictable change in the other variable
What does Pearson’s r determine?
If there is a linear relationship between variables
How to calculate total covariance?
TC(x, y) = SUM( (xi - mx) x (yi - my) )
xi - mx = difference between x co-ord and mean
yi - my = difference between y co-ord and mean
multiple = multiple the difference of the co-ord pairs
sum = add products of co-ord pairs
How to calculate sample co-variance?
C(x, y) = TC(x, y) / (n-1)
= (SUM((xi - mx) x (yi - my))) / n-1
What does sample covariance describe?
How much 2 variables co-vary (amount of variance they share)
What is positive, negative and zero covariance?
positive = higher than average values of 1 variable tend to be paired with higher than average values of the other variable negative = higher than average values of one variable tend to be paired with lower than average values of the other variable zero = 2 random variables are independent (note, not always independent, could instead have a non-linear relationship)
How can covariance and variance be related?
Var (x) = C (x, x)
How to calculate Pearson’s r?
r(x, y) = C(x, y) / sx x sy
sx x sy can also be written as: SQRT Var(x) x SQRT Var (y) SQRT C(x, x) x SQRT C(y, y)
What are the strength descriptors for Pearson’s r?
Perfect = +- 1 Strong = +- 0.7, 0.8, 0.9 Moderate = +- o.4, 0.5, 0.6 Weak = +- 0.1, 0.2, 0.3 Zero = 0
What is the null, 1-tail and 2-tail hypothesis for a correlation?
null = no correlation 1-tail = positive/ negative correlation 2-tail = a correlation
What is NHST framework for a correlation?
- formulate hypothesis
- collect data from study
- calculate Pearson’s r
- compare with p value to determine whether to reject or fail to reject null
- interpret in context
How do you calculate a p-value for Pearson’s r?
Use table
need number of tails and sample size
compare your value to value in table to see if it is significant or not (like in a t-test)
What do you need to remember when interpreting a hypothesis in context for a correlation?
Need to describe strength of correlation using the strength descriptors
e.g., r = 0.3 maybe be significant and you can reject null but it is only a weak positive correlation
How do you calculate shared (explained) variance?
(Pearson’s r)^2
= r^2
How do you calculate unshared (unexplained) variance?
1 - (Pearson’s r) ^2
= 1 -r^2
What are degrees of freedom?
related to sample size –> tells you which distribution you need to use
relates to how much data you have and therefore how good your sample statistics are likely to be
What are parametric tests?
Make certain assumptions about pops. from which data are sampled
What are 3 common assumptions that parametric tests make?
pops. from which samples are drawn should be normally distributed
variances of pops. should be approx. equal
no extreme scores
Why are parametric tests useful?
More powerful/sensitive than other approaches
What are non-parametric tests?
Make fewer assumptions about pops. from which data are sampled
Why are non-parametric tests useful?
The assumptions of parametric tests are sometimes violated
How do you take tied scores into account when ranking data?
Find the average of the ranking and then they all get the same rank
e.g., 1, 4, 4, 4, 5, 7 would first be ranked as 1, 2, 3, 4, 5, 6,
value 4 falls in rankings 2, 3, 4 so average = 3
new rankings become: 1, 3, 3, 3, 5, 6
What are Mann-Whitney U tests the NP alternative to?
Independent t-test
How do you calculate a Mann-Whitney U test?
rank data irrespective of which condition it falls in
Calc sum of the ranks in each condition (takes ties into account)
Consider what the smallest sum of the ranks could’ve been for each condition
Work out difference between smallest possible sum of ranks and actual sum for each condition
Mann-Whitney u stat = smallest difference out of the 2 conditions (U = x)
p-value calc by SPSS = exact sig (2-tailed) - compare to 0.05
if you have 1-tailed, divide p-value by 2 then compare
What is a Wilcoxon signed ranks test the NP alternative to?
Paired t-test
How do you conduct a Wilcoxon signed ranks test?
calc difference between 2 conditions (post - pre)
rank the non-zero difference scores (ignore signs but takes ties into account)
split ranks into negative and positive difference ranks (2 columns)
t-stat formed as sum of ranks of least occurring difference sign
use SPSS output for p-value –> Exact sig (1-t or 2-t) –> compare to 0.05
What is Spearman’s rho the NP alternative for?
Pearson’s R
How do you calculate Spearman’s rho?
- convert scores to ranks (rank x and y values separately)
- Calc difference in ranks (Rx - Ry)
- Square the differences
- Spearman’s rho –> p = 1 - ((6 x sum of squared differences) / n (n^2 - 1))
- use SPSS to find p-value
What values does Spearman’s rho fall between?
-1 and 1
When can we use this specific Spearman’s rho equation?
When there are no tied ranks
Why is a 1-variable Chi-squared test used?
to asses whether observed frequencies in categories are different from what might be expected
What is the DoF from a 1-variable chi-squared test?
n - 1 (n = number of categories)
What must the value of the 1-variable chi-squared test always be?
> 0
How do you calculate a 1-variable chi-squared test?
- calc difference between observed and expected (if null were true) values
- square differences
- divide squared differenced by expected value
- chi-squared stat = sum of values obtained from step above (Sum ((E - O)^2 / E)
- use DoF and sig. level in table to compare to p-value to determine if significant or not (similar to t-test)
What is a 2 x 2 chi squared test for?
asses whether there is a relationship between 2 categorical variables
How do you calculate a 2 x 2 chi squared test?
- (sum row x sum column) / total –> gives expected values for each category
- (E - O)^2 / E for each category
- sum these values to give chi squared stat
- use table to compare to p-value to determine if significant or not (like t-test)
what is the DoF for a 2 x 2 chi squared test?
(rows - 1 ) x (columns - 1)
What is a survey?
A collection of information from a sample of individuals through their responses to questions
What type of data do surveys collect?
Self report data
Qualitative and/or quantitative
Are surveys used across all research approaches? Give 3 examples
Yes
Experimental, correlational, qualitative
What are the 2 main types of surveys used?
questionnaires
interviews
True or false
Surveys are often used to operationalise constructs
True
What are 3 ways that questionnaires can be administered?
Postal
Online
In person
What are 2 ways that interviews can be administered?
Telephone
Face to Face
What are 2 uses of surveys?
Gather data e.g., on attitudes, behaviour, opinions etc.
Gather retrospective, present or future data
What are the purposes of surveys? Is there overlap?
Information gathering - exploratory or descriptive
Theory testing and building - explanatory or predictive
Usually some overlap between the 2
What are 3 general strengths of surveys?
- simple and straightforward
- easily adapted to different populations
- standardised
What is a general limitations of surveys?
- characteristics of ppts might affect data collected
e. g., memory, knowledge, experience, motivation, personality
What are 2 limitations of self-administered questionnaires?
- misunderstand questions
- response rate
What are 3 limitations of interviews?
- interviewer’s characteristics
- interaction between ppt and interviewer
- ppts might be less honest
What are 3 strengths of self-administered questionnaires?
- big sample = large amount of data
- efficient, fast, cheap
- anonymity
What are 2 strengths of interviews?
- question clarification
- interviewer can encourage involvement
What needs to be standardised in a survey? How can comparisons be made?
- measuring instruments
- what it is and how it is administered
normative data is often available to provide comparisons
What are psychometric tests? Give some examples
- standardised questionnaires/tests designed to measure particular traits/ abilities
e. g., personality inventories, cognitive ability tests, measures of MH status - items are published as an inventory
- norms are available allowing for the interpretation of individual ppt data (expressed as standardised scores)
- reliability is established but validity is sometimes questioned
When should a new questionnaire be developed?
when there are no existing tools to measure your area of interest
to avoid jangle - different labels for what are essentially the same thing
Why should questionnaires be piloted?
to identify problems and allow for revisions
to be able to gain feedback
What are 3 general design principles for questionnaires?
- keep it short
- make sure its readable (ppts can understand language used)
- provide appropriate response options (avoid forcing ppts to choose between more than 1 correct option or not having any correct options)
What is a response rate?
The percentage of questionnaires completed and returned
How can response rate be maximised?
- keeping questionnaires short, simple + clear
- include pre-paid envelopes for postal surveys
- send a reminder
- offer an incentive
What should the instructions in a questionnaire be? What does this ensure?
clear and standardised
Ensures we are measuring what we mean to and not the ppts understanding of the instructions
What should be considered in a survey concerning order?
Useful to divide into sections e.g., by topic or question type
screening if ppt is eligible should be at the start
start with easy and engaging questions
use funnelling/branching questions if appropriate –> ppts only answers questions relevant to them
What are demographics in relation to a survey?
The characteristics of the sample
e.g., age, gender, racial background, sexual orientation, religion
only include if relevant –> make sure response options are inclusive to all
What are the pros and cons of open questions?
pros:
- more detail, rich data, don’t impose assumptions
Cons:
- longer and more difficult to complete, difficult to analyse responses (often subjective)
What should be taken into consideration when considering using open questions in a survey?
- only use if justified
- ensure focus is clear
- decide on analysis strategy from outset
- more useful for descriptive and exploratory work
What are the pros and cons of closed questions?
pros:
- quick to complete, easy to analyse (objective), standardised responses
Cons:
- can impose assumptions , oversimplify complex issues
When should be taken into consideration when considering using closed questions in a survey?
- ensure questions are clear
- provide clear response options
- consider style of response options
- more useful for explanatory and predictive work
What should be avoided in surveys?
- using double-barrelled questions –> 2 separate issues but just 1 answer
- ambiguity
- negations –> negatives in statements
- double negatives
- value-laden / leading questions –> avoid emotive language / influencing ppts
- jargon
What are the 2 types of response bias?
Social desirability bias
Response acquiescence
What is social desirability bias? How can it be identified?
ppt responds in positively biased way
identify with a lie/ social desirability scale
What is a lie scale?
asks same question in different ways to see if the answer remains the same
What is a social desirability scale?
Ppts always respond with extreme answers –> can consider excluding them
What is response acquiescence? How can it be identified?
Tendency to agree rather than disagree (yes-sayers but can also have no-sayers)
Identify by including both positively and negatively worded questions as this makes ppts think about the response they are giving - don’t just answer automatically
What do rating scales do?
ask ppts to provide “how much” judgements
What is a dichotomous rating scale?
2 response options
simplest type of quantification
What is a multichotomus rating scale?
choose 1 response option
or
choose multiple response options
What is a Likert scale?
consists of a multi-point response (typically 5)
aims to ensure equal spacing of response options
What should be considered when using a Likert scale?
response acquiescence
verbal/ written responses for all or only for anchors?
inclusion of a neutral response?
What is a non-verbal rating scale?
useful with children and cognitively impaired individuals
point to the face that shows your answer
sometime necessary to include labels to more clearly define meanings for each category
What is a ranking scale?
measures the relative importance of several items
What is a graphic rating scale?
ppts mark along a continuous line which is anchored at each end
record score by measuring where line is marked
What should be taken into consideration concerning reliability and validity in a questionnaire?
reliability assessed using:
temporal consistency e.g., test-retest
internal consistency e.g., split half reliability
construct validity:
short-term can be assessed in terms of:
convergent validity –> correlates with tests of related constructs
discriminant validity –> correlates with tests of different constructs
What is a semantic differential scale?
more indirect measurement of attitude –> doesn’t assume an attitude is a cognitive belief
respondents indicate thoughts and findings by marking a response on scales between bipolar opposite adjectives
What should be taken into consideration concerning questionnaire construction?
- questionnaires can measure 1 or more variables
- typically multiple items are used to measure a single variable–> important when trying to measure fuzzy constructs e.g., attitudes
- variable scores often calculated e.g., avg./ total
- better measurements with more items but inattention may result from too many items
What should be taken into consideration concerning number of response options in a questionnaire?
too few = low sensitivity
too many = low reliability
What does ethics involve?
systematising, defending and providing standards by which behaviour can be judged as right or wrong
What are normative ethics?
practical task of arriving at moral standards that regulate right and wrong conduct
Give 10 examples of infamous unethical studies
little albert conformity line study Harlow monkey study robbers cave experiment Milgram obedience study learned helplessness study bystander effect studies blue eyes brown eyes study Stanford prison experiment monster study
What are the 2 distinct approaches to ethics?
consequentialism
deontology
What is consequentialism?
the rightness or wrongness of an act depends upon its consequences
What is a subtype of consequentialism?
Utilitarianism - emphasises the role of pleasure or happiness as a consequence of our action
What is deontology (duty)?
certain acts are right or wrong in themselves, not necessarily in terms of their consequences
What is categorical imperative?
act so that you treat humanity always as an end and never as a means only
What approach to ethics does the BPS take?
deontology
Why do we need a code of ethics?
psychological egoism - self-oriented interest ultimately motivates all human actions
What are the 3 ethical codes that are followed?
WHO guide for conducting medical research with human subjects
BPS guidelines for carrying out psychological research –> contains code of ethics and conducts and code of human research ethics
Institutional codes
What are the 4 ethical principles of the code of ethics and conduct?
respect
competence
responsibility
integrity
What are the points of consideration for respect in the code of ethics and conduct?
privacy and confidentiality respect communities and shared values within them impacts on the broader environment - living or otherwise issues of power consent self determination the importance of compassionate care
What are the points of consideration for competence in the code of ethics and conduct?
possession or otherwise of appropriate skills and care needed to serve people
the limits of their competence and the potential need to refer on to another professional
advances in the evidence base
the need to maintain technical and practical skills
matter of professional ethics and decision making
any limitations to their competence to practice taking mitigating actions where necessary
caution in making knowledge claims
What are the points of consideration for integrity in the code of ethics and conduct?
honesty, openness and candour
accurate unbiased representation
fairness
avoidance of exploitation and conflicts of interest (including self-interest)
maintaining personal and professional boundaries
addressing misconduct
What are the points of consideration for responsibility in the code of ethics and conduct?
professional accountability
responsible use of their knowledge and skills
respect for the welfare of human, non-human and the living world
potentially competing duties
What are the 4 ethical principles of the code of human research ethics?
respect for the autonomy and dignity of persons
scientific value
social responsibility
maximising benefit and minimising harm
What are the ethical standards for respect for the autonomy and dignity of persons regarding the code of human research ethics?
inform of the nature of research
avoid discriminating practices
ensure self determination (protect against coercion)
ensure privacy
What are the ethical standards for respect for scientific value regarding the code of human research ethics?
accountability for research quality
low quality research is unethical (design, valid and reliable measures)
What are the ethical standards for respect for social responsibility regarding the code of human research ethics?
purpose of research
awareness of outcomes (predicated and unexpected)
acknowledge limitations
What are the ethical standards for maximising benefit and minimising harm regarding the code of human research ethics?
assessing and identifying risk
put in place measures to minimise or manage risks
What are the 7 key practical considerations for ethics?
risk valid consent confidentiality giving advice deception debriefing professionalism
What is risk regarding the 7 key practical considerations for ethics?
potential physical/ psychological harm, discomfort or stress
all research carries some risk but this should be no greater than risks in ordinary life
Responsibility to: identify potential risks, develop protocols for risk management, inform ppts of any risks
What is valid consent regarding the 7 key practical considerations for ethics?
2 stages:
- ) instruct potential ppts of nature of study
- ) obtain written agreement to take part
ppt info form includes nature of study, any risks and benefits, procedure of anonymity, right to withdraw
What is the mental capacity assessment?
a person is unable to make a decisions if they are unable to:
understand information relevant to the decision
retain the information
use/ weight the information
communicate their decision (by any means)
What is confidentiality regarding the 7 key practical considerations for ethics?
ideally research allows complete anonymity but if not information should be kept confidential
breaching confidentially should be agreed with ppts in advance
should be no information “leaks” - intentional or unintentional
What is giving advice regarding the 7 key practical considerations for ethics?
giving advice is ethical if:
forms part of the study
agreed with ppts in advance
subject to ethics reviews in advance
if you obtain evidence of problems unexpectedly you have a duty to inform ppts to stop the endangerment of their wellbeing in future
should identify risk of evidence emerging
exercise caution if ppts ask for advice
What is deception regarding the 7 key practical considerations for ethics?
cannot deceive unnecessarily
What are the 3 types of deception?
deception by commission = actively misleading
deception by omission = failing to disclose all details
accidental deception e.g., misunderstanding of what study requires, time required, experimental extras not explained prior
What is debriefing regarding the 7 key practical considerations for ethics?
provide information to ppt about role in study both before and after
reduce any distress caused by study
active intervention
if deception was involved: provide ppts with sufficient information to fully understand the nature of the research at the earliest opportunity
threats to ethics: not providing contact details, if debriefing is not feasible
What is professionalism regarding the 7 key practical considerations for ethics?
responsibility to be honest and accurate with results
must credit to original sources of ideas –> plagiarism
must maintain original data and electronic copies of project write-up for potential verification
Why is understanding people and improving their lives a challenging goal?
peoples experiences and lives are complex
there tends to be multiple interacting causes and influences
people aren’t passive –> they are actively involved in creating their lives and experience
we can be very different from one another
can only considering quantitative data lead us to overlooking information needed to understand a problem?
yes
What are the goals of qualitative research?
- ) understanding meaning –> how people make sense of their world and experiences
- ) understand what it is like to experiences particular condition and how people manage certain situations
- ) focussed on describing and possibly explaining or interpreting
- ) studies people within naturally occurring settings to understand how experience and meaning is shaped by context
- ) asks questions about processes
Why is qualitative research an umbrella term?
covers different: research questions data analysis data collection research area
qualitative researchers make different methodological choices depending on their philosophical position
What is ontology the study of?
concerned with the nature of reality
What are the different positions in ontology?
- ) realism (quantitative) –> there is a single reality that exists independently of the researcher that can be uncovered
- ) relativism (qualitative) –> reality is constructed through interpretation so the social world is comprised om multiple realities and perspectives, each as relevant as the other
- ) subtle realism –> acknowledges existence of an independent reality but denies that there can be direct access to that reality
What is epistemology the study of?
how is knowledge created?
What are the positions in epistemology?
- ) positivist (quantitative) –> genuine knowledge is objective, observable, law-like, value free and can be uncovered through scientific methods
- ) interpretivist/ constructionist (qualitative) –> all knowledge is socially constructed, an interpretation, not value free
What is the research questions of qualitative methods?
exploratory, focussed on individual experiences, meaning and interpretation
What is the data collection of qualitative methods?
non-numeric, rich, detailed
collected in context/ natural settings
What is the data analysis of qualitative methods?
facilitates discovery of unanticipated insights, inductive, captures complexity and variation
What is the interpretation of qualitative methods?
subjective, transferrable, acknowledges the active role of the ppts and researchers in constructing knowledge
What should qualitative research questions emphasise and avoid?
emphasise –> experience, understanding and meaning
avoid –> quantification, generalisable observations and reduction of complexity
What does data collection in qualitative research aim to do?
preserve richness of individual experience
access meaning
give voice to individuals/ groups
facilitate the discovery of unanticipated insights
be sensitive to variation in experience
understand experiences in context
What are examples of unobtrusive methods? What are the pros and cons?
published narratives, archival docs, observations, images, audio, self-report
pros –> naturalistic
cons –> limited ability to probe in order to gain deeper understanding
What do interviews do?
tap into lived experience
professional conversation with a purpose
conversation guided by schedule/ topic
What are structured interviews?
follows interview schedule same questions, order and setting may have suggested response options answers can be coded and quantified for statistical analysis interviewee has passive role
What are the pros and cons of structured interviews?
pros –>
standardised, consistent, low bias
reliable and replicable
quick and doesn’t require strong interview skills
cons--> not qualitative closes off theoretical avenues limited range of responses difficult to capture complexity
What are semi-structured interviews?
use schedule flexibly –> follow up probes and can change order or questions to be more appropriate to ppts ideas
guided conversation
questions mostly open but some can be closed
important to build rapport at start of interview
What are some pros and cons of semi-structured interviews?
pros --> richer detail and understanding some standardisation possible captures complexities and inconsistencies provides insight into experiences useful for sensitive topics gives a voice to ppts
cons –>
non-natural conversation
What is an unstructured interview?
topic guide but interviewee led
interviewer acknowledges they don’t know in advance all issues / questions
they develop and adapt questions and follow-up probes that are appropriate to the situation
What are some pros and cons of unstructured interviews?
pros –>
empowers interviewees to define and focus on what’s important to them
useful when little is know about the topic/ target group are hard to reach
gives a voice to ppts
rich, detailed and complex data
cons --> need good interview skills little standardisation and reliability complex to analyse potential for bias
What is a focus group?
topic guide but ppts interact with each other and moderator about statements
group dynamics are integral to process of data generation
meanings are jointly constructed
group can be homogenous or heterogenous
often video recorded
requires a skilled moderator
What are some pros and cons of focus groups?
pros –>
have higher ecological validity –> more naturalistic
gain different perspectives on a topic
collect large amounts of data in a short space of time
relatively inexpensive
cons –>
not always suitable for sensitive topics
video recording can reduce quality of group interaction
social desirability bias
groups dynamic –> power issues
ethical issues
How should you construct an interview schedule?
- ) identify relevant topics and questions
- ) phrase questions in a way that encourages detail –> include probes
- ) use logical order e.g., easy to hard questions, leave sensitive topics until the end
- ) consider how to build rapport –> make ppts comfortable, allow ppts to set expectations (e.g., are there breaks, how long will the interview be), use accessible language
What should be avoided when constructing an interview schedule?
avoid: leading and closed questions judgement or critical questions complex and double barrelled questions jargon and technical language
What is an interviewers role in an interview?
encourage interviewee to speak
interviewer talks less and asking probing questions
interviewer creates conditions that help the interviewee give detailed and honest description of experiences
What should an interviewer plan to do in an interview?
create a safe environment
address ethical issues
care for interviewees wellbeing
be flexible and self aware
Why is it important to be aware of non-verbal communication in an interview?
to be able to convey interest but maintain boundaries
to avoid conveying judgement
how can language be used effectively in an interview?
positive encourages
probes and prompts to seek clarity and deeper understanding
silences
avoid premature closure
What is qualitative data analysis?
sets procedure used flexibly identifies patterns - usually inductive describes and interprets data empathetic needs active engagement of the researcher with the data
What is transcription?
first part of data analysis
turning speech into written word
Are there different types of transcription?
yes
orthographic (most common) –> speech is transcribed verbatim using standard spelling conventions
Jefferson system (more complex) –> includes phonemic, non-phonemic and non linguistic aspects
What is content analysis?
examines patterns in systematic matters and analyses statistically
not typically considered qual
What is grounded theory?
generates theories of social phenomena through systematic data analysis
has inductive and deductive stages
What is conversation analysis?
identify rules of conversational organisation
studies natural conversation to discover how ppts understand and respond to each other
What is interpretative phenomenological analysis?
how a given person, in a given context, makes sense of a given phenomenon (of personal significance e.g., a major life event)
uses small homogenous samples
What is thematic analysis?
identifying, analysing and reporting patterns
describes data in rich detail
may also interpret data
What are some key features of thematic analysis?
flexible, easy and quick
accessible to novice researches
summarises key features of a large body of data
highlights similarities and differences
generates unanticipated insights
interprets data
accessible to educated general public e.g., informing policy
What are the 6 phases of thematic analysis?
- ) data familiarisation
- ) generating codes
- ) searching for themes
- ) reviewing themes
- ) defining and naming themes
- ) producing report
What is orientating the analysis in thematic analysis?
due to its flexibility, you must state which theoretical framework you are using in your analysis
What is data familiarisation in thematic analysis?
reading and re-reading data
data immersion
keep RQ in mind
What is coding in thematic analysis?
identify features of data (sematic or latent)
codes should be able to be understood independently of data
1st order (semantic) and 2nd order (latent) codes
codes should shift towards systematic engagement with data
no definitive set of codes
should create coherent set of codes
often code and recode
What is searching for themes in thematic analysis?
central organising concept - brings codes together (coherent story)
active and constructive phase of analysis
tentative to start (candidate themes)
use post-it note approach –> grouping and regrouping codes until all fit
What is reviewing themes in thematic analysis?
checking quality of themes
does it:
cover multiple interviewees?
have a central organising concept with no overlap?
answer the RQ?
capture all codes?
is there a clear fit between themes and data?
What is defining and naming themes in thematic analysis?
should be concise, informative and catchy
though each theme is distinct, they should form an overall story
What is theme writing in thematic analysis?
- determine exact story told by each theme and overall
- describe data and why it is important
- select data from across extracts for evidence
- provide interpretation of data
- write a theme definition –> extended central organising concept
Is there a consensus for how to assess the quality of qual data?
no there are different views
What did Yardley propose to evaluate qual quality?
a set of flexible principles
What are the 4 principles that Yardley proposed to assess qual quality?
- sensitivity to context
- commitment and rigour
- transparency and coherence
- impact and importance
What is sensitivity to context (qual quality)?
awareness of broader context that research is conducted in
How can sensitivity it context be achieved (qual quality)?
- outline relevant lit.
- outline common sense concepts and assumption e.g., philosophical stance
- outline socio-cultural setting (of allt ppts and researcher)
What is commitment and rigor (qual quality)?
- completeness of data collection
- completeness of analysis
- triangulation
- validation –> checking interpretation of data with others
How can completeness of data collection be achieved (commitment and rigor (qual quality))?
- samples are purposive –> collect enough data to address RQ
- aim for data saturation –> the point where no new ideas are drawn from the data
How can completeness of analysis be achieved (commitment and rigor (qual quality))?
- aim for complete interpretation that addresses variation and complexity within the data
How can triangulation be achieved (commitment and rigor (qual quality))?
- might involve getting data from various sources
- might involve combining analytic approaches
How can validation be achieved (commitment and rigor (qual quality))?
- peer verification –> analysts working together to check interpretations are plausible
- respondent verification –> checking with interviewees, they comment on how well the interpretations fit with their experience
What is transparency and coherence (qual quality)?
Transparency:
- auditability –> reader understands how data became eventual findings and be able to discern the patterns themselves
- Reflexivity
Coherence:
- coherent narrative
How is auditability achieved (transparency (qual quality))?
- method section details every aspect of data collection, rules used to code and how stages of the analysis progressed
- findings include excerpts of data
How is reflexivity achieved (transparency (qual quality))?
- discussion of motivations –> assumptions, intentions, actions
- include reflexive statement
How is a coherent narrative achieved (coherence (qual quality))?
- discussion links findings back to existing knowledge
- good fit between RQ, philosophical perspective and method of investigation
How is impact and importance achieved (qual quality)?
- discussion explains why findings are important and the potential impact
- impacts include theoretical, practical and socio - cultural
What is impact and importance (qual quality)?
- potential impacts
- transferability to other contexts with other people
How can transferability be facilitated (impact and importance (qual quality))?
- facilitate by giving full, thick descriptions of ppts
- ultimately user of research decides transferability
What are mixed research methods?
- systematic
- qual and quant methods with intention to engage multiple perspectives
- produces findings that are greater than what can be produced separately by its parts
What 2 analytical logics do mixed methods research embrace?
- ) an exploratory/ hypotheses generating one
2. ) a confirmatory/ hypotheses confirming one
What is the prevalence of mixed methods research?
- 18% in all fields
- 7% in top tier psych journals
- 13.7% in psych journals with an applied focus
- is on the increase
What is the purpose of mixed methods research?
- ) Triangulation –> increases confidence
- ) Complementary –> different aspects of same phenomena, broadens conclusions
- ) Dev. –> results from one inform dev. of other
- ) initiation –> diff methods used to investigate diff aspects of same phenomena
- ) Expansion –> diff methods used to assess diff phenomena to expand scope
What is mixed methods research considered in terms of?
order and dominance
What is Morgan’s priority sequence model?
Different orders and dominance of mixed methods research:
- equal and concurrent
- equal and sequential
- dominant and concurrent
- dominant and sequential
What are the design decisions for mixed methods research led by?
- led by RQ and current knowledge
Quant = existing knowledge
Qual = exploratory insights
