Research Methods Summary

Major features of science:

• Empiricism
• Control
• Objectivity
• Theory
• Replicability
• Construction

Scientific Process:

• Induction: Reasoning from particular to general
• Deduction: Reasoning from general to particular 

Evaluation:

• Scientific Research is Desirable
• Psychology shares to goals of science
• Kuhn - no single paradigm
• Lack of objectivity and control leads to experimenter bias and demand characteristics

Are goals of science appropriate?

• Nomothetic vs Idiographic
• Qualitative research - triangulation 

Links:

• Reductionist - reduces complex phenomena to simple ones
• Deterministic - searches for casual relationships 

Peer Review:

Serves three main purposes:

• Allocation of research funding
• Publication of scientific journals
• Research assessment exercise 

• Research published on the Internet requires new solutions 

Evaluation:

• May be an unachievable ideal
• Anonmity allows honesty and objectivity
• Publication bias favours positive results
• May lead to presevation of the status quo 

Conventions of Scientific Reporting:

• Abstract - summary of study
• Introduction/aim - literature review and research intentions
• Method - procedures and design of study
• Results - descriptive and inferential statistics
• Discussion - outcomes and implications of study
• References 

Links:

• Some changes in science are not logical changes but represent a shift in perspective
• Burt research - an example of scientific fraud 

Experiments:

• IV varied to see effect on DV
• Laboratory experiment - high on internal validity, low on external validity
• Field experiment - more natural environment but more issues of control than lab experiment
• Natural experiment - uses naturally occuring IVs but cannot conclude causality
• Experimental designs - repeated measures, independent groups, matched pairs 

Self-Report Methods:

• Questionnaires and Interviews
• Structured - more easy to repeated
• Unstructured - questions that evolve are dependent on answers given
• May involve open or closed questions
• Main problem = social desirability bias 

Observational Studies:

• Observing behaviour through behavioural categories 
• Sampling methods - time and event sampling
• Open to subjective bias - observations affected by expectations 

Correlational Analysis:

• Concerned with relationship between two variables
• Does not demonstrate casuality 
• Other variables may influence any measured relationship 

Case Studies:

• Detailed study of individual, institution or event
• Generally longitudinal, following group or individual over a long period of time
• Allows study of complex interaction of many variables
• Difficult to generalise from specific cases 

Reliability:

• Experimental Research - allows for replication of study
• Observations - inter-obsever reliability can be improved through training
• Self-report - internal reliability and external reliability 

Validity: 

• Internal validity - test what we intended to test?
• External validity - can results be generalised?
• Lab experiments not necessarily low in external validity
• If low in mundane realism, reduces generalisability of findings
• Observations = internal validity affected by observer bias
• Self-report techniques = face and concurrent validity 

Sampling Techniques:

• Opportunity - most easily avaliable participants
• Volunteer - through advet but subject to bias
• Random - all members of target population must be equal chance of selection 
• Stratified and quota - different subgroups with sample, leads to more representative 
• Snowball - researcher directed to other similar potential participants 

Ethical issues with Humans:

• Informed consent and deception
• Harm - what is too much?

Code of Conduct:

• Respect for worth and dignity of participants
• Right to privacy, confidentiality, informed consent and right to withdraw
• Intentional deception only acceptable in some circumstances
• Competence - retaining high standards
• Protection from harm and debriefing 
• Integrity - being honest and accurate in reporting
• Use of ethical guidelines in conjunction with ethical committees
• Socially sensitive research - potential social consequences for participants 

Ethical Issues with non-Humans:

• Reasons for animal use - offers opportunity for greater control and objectivity
• Moral issues - sentience (experience of pain/emotion)
• Specieism - form of discrimination against non-human animals
• Animal rights - Regan (1984), no animal research is acceptable
• Do animals have right if they have no responsibilities?
• Animal research subject to strict legislation (Animals Act; BPS guidelines)
• The 3 R's - reduction, replacement, refinement 

• Probability = likelihood that a pattern of results could arise by chance
• If probability extremely unlikely, then result is statistically significant 
• Inferential tests determine whether chance or real trend in data
• Probability levels represent acceptable level of risk of making a type 1 error
• More important research, more stringent significance levels
• Type 1 error = null hypothesis is rejected when true
• Type 2 error = null hypothesis is accepted when false 

Inferential Tests 

• Different research designs require different tests
• Different tests for different levels of measurement (nominal, ordinal, interval, ratio)
• Tests yield observed values, and then compared to CV to determine significance level
• One tailed = directional
• Two tailed = non-directional

Spearman's Rho: 

• Ordinal data
• Predicts correlation between two variables
• Each person is measured on both variables 

Chi-Squared:

• Nominal
• Predicts differences between two conditions between two variables
• Data is independent

Mann-Whitney U

• Predicts diffeence between two sets of data
• Independent groups design
• Ordinal

Wilcoxon-T

• Difference between two sets of data
• Repeated designs or matched pairs
• Data at least ordinal 

Central Tendancy:

• Indicates typical or 'average' score
• Mean = sum of all scores divided by number of scores
• Median = middle value in ordered list of scores
• Mode = most common value 

Measures of Dispersion:

• Indicate spread of scores
• Range = difference between highest and lowest score
• Standard deviation = spread of data around mean

Graphs:

• Bar chart = illustration of frequency, height of bar represents frequency
• Scattergram = illustration of correlation, suitable for correlational data 

Key points:

• Quantitative = not relevant to 'real life'
• Qualitative represents world as seen by individual
• Emphasises collection of subjective information from participant
• Data sets tend to be large
• Qualitative data cannot be reduced to numbers
• Can be examined for themes 

Methods:

• Coding using top-down approach (thematic analysis) = codes represent ideas/themes from existing theory
• Coding using bottom-up approach (grounded theory) = codes emerge from data
• Behavioural categories used to summarise data
• Reflexivity indicates attitudes and biases of researcher
• Validity demonstrated by triagnulation
• Reliability checked by inter-rater reliability