Specialized Designs Flashcards
Quasi-experimental designs and ex post facto designs
- used when something is missing…
- typically control groups and/or random assignment of subjects
Major categories of designs
- pre-experimental: no control groups and no random assignment of subjects to conditions. Acceptable for pilot research only
- experimental: controls groups, random assignment of subjects to conditions
- quasi-experimental: often control groups, but no random assignment of subjects to conditions. Often take advantage of naturally occurring events- lack of control over variables
- ex post facto: special case of between subject design. Here we extract a correlation between variables, not causation
Quasi-experimental designs
- dont fill requirements for a true analytic experiment
- issues with:
- internal validity
- external validity
- random selection not possible or not respected
Quasi-experimental design examples
- useful when statistical power is an issue
- when few measurements are possible
- when availability of participants is limited
- random assignment of participants not possible
- common mistake: pooling fallacy (compensating for lack of subjects by collecting more data
- eg. Jet lag study issues:
- Finding participants involved in jet lag travelling willing to participant
- Variation in duration and distance of travel (#of time zones), departure and arrival times, direction of travel, sleep pattern/strategy before leaving for trip etc
- solution: within-subject design (all participants go through all treatments
- problems: order effects… solution: counterbalancing
Counterbalancing
- when order effects may affect results
- splitting groups so that half get one treatment first, and others get other treatment first to see if there is a difference in order
- making order a factor
Ex post facto
- researcher arrives after the fact. Nature has implemented treatment (groups are based on natural occurrences that make them distinct)
- different environments (environmental or Contextual factors)
- different dispositions (dispositional or individual factors
Prospective vs retrospective ex post facto
- prospective: looking for effect of certain cause (i.e. have cause and look for the effect)
- longitudinal study of individual to see effect
- cohort designs
- retrospective: have effect, but looking for the cause of it
- investigate past of individuals who suffer given effect
- case control designs or criterion group designs
Characteristics of EPF designs
- participants selected after the fact for 2 reasons:
- Ethics (invasive studies)
- Subject variables (gender, age, education level, personality traits etc) become independent variables (treated as treatment condition)
- rationale: cannot randomly assign people to different age groups etc
Prospective EPF internal validity issues
- no random sampling from population
- no random assignment conditions
- confounded variables typical to the groups investigated (eg. High stress job participants smoke and drink more)
- selection of subjects becomes complicated and strict criteria applied
- convenience sample problematic (criteria themselves may be confounds)
- eg. Air traffic controllers exposed to radiation from equipment
- detection bias: common in biomedical research
- probability that members of a certain group are diagnosed because of the nature of their job (i.e. air traffic controllers more likely to be medically assessed than a hobo)
- accurate identification of members of respective groups based on criteria
- eg. Finding people with GAD may be much easier than finding people with BPD
Prospective EPF external validity issues
- choice of groups:
- cant generalize from one group/occupation to another… ATC doesnt necessarily represent ALL high stress jobs for example
- does the choice of group (eg high stress job) represent well with people with chronic stress (in general)
- does occupational stress differ from domestic/personal stress?
-longitudinal nature of the study: issue of experimental mortality or attrition
Solutions for prospective EPF design external validity issues
- matching: making sure that the groups do not differ on any other variable than ones selected
- subject to subject matching of characteristics
- distribution for distribution matching for descriptive statistics, mainly central tendency or variability
- measure the variables: identify possible confounding variables and measure them to determine if they have effect or not
- methods of analysis of covariance can help
Retrospective EPF designs
- common in health research
- similar problems as prospective designs
- comparative advantages:
- smaller number of subjects required
- shorter time period
- less money required
Specific issues with retrospective EPF designs
- present context motivating the investigation
- detection bias
- historical issues in diagnosis and awareness
- diagnosis likely made by different parties/doctors
- differential assessment or perspective on stress between cancer group and healthy group
- less extensive records in healthy group
Solutions
- matching and measuring confounding variables
- can be difficult because you must search back in time and you rely on memory of subjects and their families etc, which affect accuracy and completeness
Change
- studying changes in time of structures and processes
- ontogenetic changes: developmental research
- changes in the individual neuron, brain, animal, person
- historical change: cross-generational research
- changes across generations (strains, families etc)
- phylogenetic change: evolutionary research
- changes in species and populations: speciation, natural selection
Developmental: longitudinal
- example: social play development in children
- longitudinal approach: same individual or group are tested, measured repeatedly over long period of time
- disadvantages: test conditions become well known by children
- are performance or behavioural changes due to experiment or maturation
- long time period and money
Developmental: cross-sectional
- example: social play development in children
- approach: measuring different individuals at different ages and at the same time
- disadvantage: individual differences can account for some effects and differences in development
- solution: hybrid version (cohort sequential/ cross sequential
Comparative/evolutionary
- common in:
- comparative and evolutionary neuroscience
- comparative and evolutionary psychology
- ethology, behaviour ecology
- cross cultural psychology, anthropology, ethnology
- Linguistics
- guiding principle: compare and contrast
- theoretical foundations: natural selection and culture
Objective of nested designs
- allows us to test 2 things:
- Difference between control and study areas
- The variability of the sites WITHIN ares
- if we fail to find a significant variability Among the sites within areas, and find a significant different between areas, we would know there is an environmental impact
- but it is likely that you WOULD find variability within the sites of one area
- if so, you can still test to see whether the difference between the areas is significantly larger than the variability among sites within areas.
What is nested
- nesting tasks
- nesting groups (naturally occurring groups)
- nesting locations, sites, areas (naturally occurring sites)
- nesting times (centuries, decades, years, seasons, months etc)
Time series designs
- basic time series with intervention:
- multiple observations before and after treatment, and observation during treatment
-interrupted time series: same but with naturally occurring event… often taking something away
Time series design variations
- give treatment early, then cancel it and see effects
- must consider carryover effects
- cancellation of drugs cold turkey can be dangerous … discovered through time series
-follow typical ABA design (or variations of this theme)
No equivalent control group design
- using time series design but two separate groups:
- one that receives treatment, and one that doesn’t
- still need similar groups (matching) for internal validity
Pre-test/post-test designs
- true experimental design, similar to within-subject
- two levels: pre and post treatment
- carryover can be a problem
- must have control groups and random assignment if possible
- pre test should be same for both conditions, only post test should yield different results
- problem: effect of having experienced pre-test may affect results
- two solutions:
1. Eliminate pre-test completely
2. Solomon 4-group design: partial removal of pre-test to evaluate if there is an effect of the pre-test- if results from all groups are different you know there is a pre-test affect
- two solutions: