1
Q
Types of sampling in observation
A
- Time sampling
- Event sampling
- Situation sampling
- Subject sampling
2
Q
Observation methods
A
Direct observation - intervention & non-intervention
Indirect observation
3
Q
Observation with intervention
A
Participant observation - disguised & undisguised
Structured observation
Field experiment
4
Q
Problems with observation
A
Reactivity
Demand characteristics
5
Q
Combatting reactivity
A
- concealing observer’s presence
- adaptation (habituation, desensitization)
- indirect observation
6
Q
Types of interview methods
A
- Completely unstructured
- Unstructured
- Semi-structured
- Structured
- Completely structured
(know each description)
7
Q
Guidelines for designing an interview
A
Giving information at the start Assuring anonymity Achieving and maintaining rapport Using familiar language Neutrality and non-judgementality Active listening Showing interest Nonverbal communication Natural questioning
8
Q
Basic components of TA
A
Transcribing textual material
- Put the verbal data into words
- Increases familiarity with the text
Analytic effort
- Becoming increasingly familiar with the text
- Detail with which the data is studied
- Extent to which researcher processes and reprocesses the data – to recheck themes found, etc.
- Presented with difficulties that must be resolved
- Check and recheck the fit of the analysis
Identifying themes and sub-themes
- Label categories of data that fit together and refine themes
9
Q
Adv and disadv of TA
A
Good method for novices because:
- Atheoretical – no particular theoretical orientation is associated with it
- Flexible – freedom to perform analysis their own way; most accessible
- Contains the core elements of the data analysis procedure used in several other more complex qualitative approaches; base on which other analysis methods are developed
Disadvantages
- Lacks transparency – no steps to be followed; reviewers can’t check the processing of data
- Researcher may just point out obvious facts and exclude details
10
Q
Stages in sophisticated version of TA
A
- Familiarization with data
- Initial coding generation
- Search for themes based on initial coding
- Review of the themes
- Theme definition and labelling
- Report writing
11
Q
Content Analysis
A
- Quantify qualitative data so you can move ahead with analysis method
- Analyzing text to determine the frequency of appearance of words or their synonyms
- Roots remain firmly in a quantitative, positivist approach
- Used to test hypotheses, a lot in social psych
- Useful for large amounts of archival data
12
Q
Coding units in content analysis
A
Item categories identified in qualitative data; provides rate of occurrence of diff sorts of content
- Words
- Themes
- Items
- Characters
- Time & space
13
Q
Grounded theory
A
Consist of systematic inductive guidelines for collecting and analyzing data to build middle-range theoretical frameworks that explain the collected data. Throughout the research process, grounded theorists develop analytic interpretations of their data to focus further data collection, which they use in turn to inform and refine their developing theoretical analyses.
14
Q
Features of grounded theory
A
- Theory development and data collection go hand in hand
- No preconceptions help while analyzing the data in the beginning
- Constant comparative analysis – researcher keeps checking and comparing data
- Reforming of the question based on the emergent theory
15
Q
Emergent theory
A
What develops as the data are analyzed and as further data gathering proceeds as a consequence; analysis proceeds along with data gathering.
16
Q
Define qualitative methods
A
- A set of procedures designed to describe and interpret the experiences of participants in a context specific setting
- Focusses on meaning of action in a social context and not isolated setting
17
Q
Reflexivity
A
Researcher’s reflecting upon one’s own influence in the process of data collection and analysis
18
Q
Features of non-experimental research
A
- Description & interpretation of behaviour
- Behaviour as holistic, not isolated
- Follows less rigid system
- Not interested in cause-effect; focus on ‘why’
- Inductive approach
- Relationship exists between researcher and participants
- Reflexivity
- Study new behaviour and then generalize
- Complete understanding of richness of data
19
Q
Epistemology
A
Concerned with the theory of knowledge and how knowledge is constructed
20
Q
Features of positivism
A
- Objective reality exists
- Observation of observable facts for valuable accumulation of knowledge
- Straightforward relation between the world, our perceptions and understanding it
- Root of scientific method
- Direct correspondence between things and its perception (what I see is what exists)
- Goal – to produce objective knowledge that is impartial and unbiased
21
Q
Limitations of positivism
A
- Experiences of the world are not consistent or unchanging
- Our understanding of the world is actually partial and not JUST what we see
22
Q
Features of critical realism
A
- There are different views of reality
- Reality is viewed through an infinite regress of windows (the windows is a social context through which reality is seen) (take it as a lens through which you see things)
- Interpret data to understand the underlying structures – go through the layers that could impact it
23
Q
Features of phenomenology
A
- Reality is subjective
- Understand experience rather than what causes events; prime focus on what the participant says
- Role of researcher resembles that of a person-centred counsellor
- Interest in the experiential world of the participant
- The question you’re asking is – how is THIS participant experiencing the world.
- Belief that what can be the same event is experienced differently by different people.
24
Q
Features of social constructivism
A
- Knowledge is constructed by society; reality is constructed
- Major importance on LANGUAGE and all human experience is mediated by language
- Because of devlp of language, diff world views were constructed
- Used to study a discourse that constructs reality, rather than reality constructing how we talk about it
- The way people talk about the world, leads to a construction of the social reality
25
Characteristics of a qualitative researcher
- They reject positivism
- They adopt relativist position of no fixed ‘reality’
- They use relatively unstructured data collection methods
- They are concerned to capture the individual’s perspective
- They use highly detailed data analysis methods
- They use richly descriptive data
- They take the postmodernist (who doesn’t believe in positivism) perspective in general
- They believe that reality is constructed socially/individually
- They choose rich and deep data rather than hard (numerical) data
- They tend to be closer to their research participants
- They often see themselves as insiders of what is being studied
- They are concerned with interpretation over causal sequences
- They largely reject hypothesis testing
- Their theory emerges from close analysis of data
- They take a idiographic approach which focuses on the individual
26
Stages in content analysis
- decide on what material to sample and code
- decide coding units
- rank and categorise items
27
Purposive sampling
Used in grounded theory
| The researcher looks only for certain kinds of data from certain kinds of people
28
Negative case analysis
Used in grounded theory; search for cases with a poor fit to the category system, so that it can be further amended and refined
Implementing principle of falsification
29
Key components of grounded theory analysis
- Comparison
- Coding/naming
- Categorization
- Memo writing
- Theoretical sampling
- Lit review
30
Features of Interpretive Phenomenological Analysis
- Analyse and present an account of the ways in which people experience specific and important events in their lives, from the participants own perspective
- First-person account is always required; semi structured interviews (mostly)
- Depends very heavily on the philosophical principles of ‘phenomenology’
- Exploratory & relativist
31
Philosophical foundation of IPA
- Phenomenology
- Symbolic interactionism
- Hermeneutics
- Idiography
32
Steps in data analysis of IPA
- Initial familiarization with a case and initial comments
- Stages in familiarization (descriptive, linguistic & conceptual)
- Initial identification of themes
- Looking for connection between themes
- Producing a table of themes
- Continuing this process with further cases
- Writing up the analysis
33
What is a hypothesis
Hypotheses are general statements/claims about the world that are derived from more broader theories.
34
What is research
A systematic inquiry that allows us to describe, explain, predict and control behavior.
35
Illusory correlation
Seems like there is a correlation but no actual correlation
36
Scientist-practitioner model
- Integrating research and clinical practice; trained professional psychologists should be knowledgeable in both research and clinical practice
- Treating each client as a scientific exercise
37
Scientific method
Merger of two historical models of science, the empirical method and the hypothetico-deductive method
38
Empirical method
- Means 'though experience'
- Gathering data, directly through experience and external senses, with no preconceptions
- Seeing what relationships appear to exist within our data
39
Hypothetico-deductive method
- A method in which theories are evaluated by generating and testing hypotheses.
- It is a method of recording observations, developing explanatory theories, and testing predictions from those theories
40
Basic principles of scientific method
- Empiricism
- Determinism
- Parsimony
- Testability
- Hypothetico-deductive method
41
Concept of falsifiability
- Principle that theories must be defined in a way that makes it possible to show how they could go wrong.
- A challenge is far more useful than repeated confirmations
- For any theory to count as a scientific theory, need see how it could be falsified.
- If it is not possible, then it is not a theory fit for science.
42
The scientific method
An abstract concept that refers to the ways in which questions are asked and the logic and methods used to gain answers. It has two important characteristics:
- Reliance on empirical method/approach
- Skeptical attitudes of scientists adopt towards explanations of behavior and mental processes
43
Null hypothesis
- States that there is no relationship between two variables
- Framed as a negative sentence (uses not or no).
- It is a hypothesis that a researcher tries to disprove to demonstrate statistical significance between variables
44
Ethnocentrism
- Attempt to understand behavior of an individual from a different culture through the framework of your own culture
- Biases arise if cultural gap is not acknowledged
45
Ways to reduce ethnocentrism
Conducting a cross cultural study
Different cultures participate in the research process, otherwise error of ethnocentrism arises. (i.e. if you want to study an idea, take representative participants from different cultures/countries and you gather data from them)
46
Replication
Process of repeating research to determine the extent to which findings generalize across time and across situations (finding same results each time)
47
Why is replication important?
- Adds information about the reliability of the conclusions drawn from the data
- In psychology, claims are made about the extremely varied and flexible behavior of humans.
- People are complex and there are many people of different types.
- We can only make estimates from samples of people’s behavior, we cannot test everyone.
- We have to generalize from small samples to whole populations.
48
Types of replication
Exact & conceptual
49
Advantages of replication
- protects against false positives (seeing a result that is not really there)
- increases confidence in the fact that the results actually exist
50
Replication crisis
- Many studies in psychology do not replicate; raises questions about the scientific process in general.
- People have the right to know whether they can trust research evidence
- Non-replicable research indicates the possibility that the original research was not done correctly
51
Priming
Process when an individual’s exposure to a certain stimulus subconsciously influences his or her response to a subsequent stimulus
52
Criticisms and challenges to scientific method
- Inadequate to capture complexities of human behavior
- Dignity as a non-scientific discipline
- Phenomenological approach
- Decline effect
- Replication crisis
- File drawer problem
- Research malpractice
53
Decline effect
Occurs when scientific claims receive decreasing support over time; difference in effect size between initial studies and later studies
54
Effect size
Magnitude of effect of the independent variable on the dependent variable
55
Causes for error in effect sizes
- underpowered studies
- publication bias
- selective reporting
56
Types of decline effect
- Inflated decline effect
- Underspecified decline effect
- False positive decline effect
- Genuine decrease effect
57
Harking
Form of research malpractice; hypothesizing after results are known
58
Forms of research malpractice
- Harking
- P-hacking
- Outcome reporting bias
- Optional starting and stopping points
59
P-hacking
- Doing different tests (multiple analyses and different tools) till you get an acceptable/significant result
- Hacking the p-value
60
Outcome reporting bias
- Selective or distorted reporting of results (either by overlooking or using a particular method)
- Eg. taking 2-3 variables into account, when one is significant and one is not, I only report the significant one.
61
Underpowered studies
Common tendency for studies to use underpowered designs. With smaller N’s or sample sizes, the probability greatly increases that a positive experimental result was inflated by error variance.
(smaller sample sizes were probably used in initial studies which had larger effects, later studies use larger samples and thus show smaller effects)
Fuels declining effect sizes
62
Sampling frame
Defining what part of the population you want to work with; the target population
63
Sampling error
Difference between mean of sample and mean of population; skewed data usually means sampling error
Occurs if data is not variable enough; larger sample size = greater variable data = reduce overall error
64
Sampling bias
Over-representation of one particular category of people
65
Operational definition
Explains a concept solely in terms of the observable procedures used to produce and measure it
66
Probability sampling
- Completely random
- Each participant has an equal chance of being selected
- High representativeness
- High generalizability
- Impractical
67
Types of probability sampling
- Simple random sampling
- Systematic random sampling
- Stratified random sampling
- Cluster sampling
68
Simple random sampling
Every member from a population has an equal chance of being selected.
69
Systematic random sampling
Every member has an equal chance of being selected, but there is a fixed interval to selection
70
Stratified random sampling
Divide a population into subgroups or strata, and from the strata, determine the few people wanted from each group.
71
Cluster sampling
Divide the population into groups or categories. Instead of assigning numbers and selecting individuals, you pick the whole subgroup.
Eg: If your study is on google employees, and there are offices all over the country, you can choose only 3 cities
Does not always represent entire population
72
Non-probability sampling
- Not random
- Based on researcher’s judgement
- Low representativeness - the sample is pre-determined i.e. you may just go to your friends, or some other people, which may not be representative.
- Low generalizability
- Convenient
73
Types on non-probability sampling
1. Availability sampling
2. Quota Sampling
3. Snowball Sampling
4. Purposive Sampling
5. Critical Cases
6. Voluntary response
74
Quota sampling
Similar as stratified sampling (randomly selected); but in quota sampling it depends on the researcher, the researcher may want to select the person or not.
75
Purposive sampling
Sample is representative of the purpose of the study; used a lot in qualitative research
76
Critical cases
Take only one person, take something not-normal, understand it to study the normal behavior
Eg: - Want to know how a person with eyesight issues, I will take someone who has issues with eyesight to figure out what is normal
77
Discourse Analysis
- Involves analysis of speech, text and conversation
- Preferred material is naturally-occurring conversation or speech; can also be performed on interview data, written form, etc.
- Used specifically if you want to understand the use of language as a social action
- Originates in the fields of linguistics, sociology, philosophy
Xaviers Sem 1
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