I have made a full summary of all important concepts from the Kazdin Chapters relevant to the ECP exam as well as the additional paper about Event Occurence. I have made sure that key concepts are easy to find by capitalizing them and I have referred to important tables in the book and their page n...
- Better design Competing explanations become less plausible
INTERNAL VALIDITY: Does the intervention account for the results?
- To what extend are other possible explanations for the results ruled out?
- Threats (Table 2.2, p.39)
o HISTORY: Events that happen independent of the study, to all participants
Protect: Control group & Randomization
o MATURATION: Changes resulting from processes within the subjects
The longer the study, the bigger the impact
Protect: Control group & Randomization
o TESTING: Change due to repeated assessment
Protect: Control group & Randomization
o INSTRUMENTATION: Changes in measurement instrument or procedure
Bigger problem if human observer
RESPONSE SHIFT: Participants’ internal standards of measurement change (they
alter their definition of what a problem is over time)
Protect: Standardized, automated assessments
o STATISTICAL REGRESSION: Extreme scores regressing towards the mean at the next
assessment
Protect: Control group & Randomization; Measurements w/ high validity &
reliability; two pre-tests & select only those who scored extreme both times
o SELECTION BIAS: Differences between groups before the start of the intervention
Protect: Randomization
o ATTRITION: Loss of subjects changing random composition of the groups
Prevent drop out: Rewards, close contact
Statistical methods to control for attrition
o DIFFUSION OF TREATMENT: Participants receiving treatment of the other condition
SPECIAL TREATMENT: Control group receiving some special treatment (e.g. extra
money because they were in the control group).
Protect: Monitor conditions
EXTERNAL VALIDITY: Can the results be generalized?
- Threats (Table 2.3, p.53)
o SAMPLE CHARACTERISTICS: Results restricted to sample with specific characteristics
WEIRD subjects
, Convenience sample
Inclusion criteria (e.g. specific disorder)
Protect: Give reasons for choosing particular sample & select consistent subjects
o NARROW STIMULUS SAMPLING: Results restricted to small range of stimulus
characteristics
The more specific the stimulus the more factors might change your results
(stimulus could be a picture that’s shown, prayer, or a therapist that’s
administering the intervention)
Protect: Present at least 2 stimuli that vary slightly in their characteristics
o REACTIVITY OF EXPERIMENTAL ARRANGEMENTS: Results not generalizable to subjects
that are unaware that they’re participating in a study
Protect: Make the purpose of the study less clear
o REACTIVITY OF ASSESSMENT: Results not generalizable to subjects that are unaware
that they’re being assessed
Obtrusive assessment: Subjects are aware that their performance is being
assessed
Reactive measures: Awareness causes different responses
Protect: Measures where purpose is less clear; test implicit attitudes; biological
measures; different types of assessment (e.g. self-report & direct observations)
o TEST SENSITIZATION: Results not generalizable to subjects that were not previously
assessed
Pre-test measurement sensitizes subjects to experimental manipulation
Changes how they react to the manipulation
Protect: Measures that are less likely to sensitize subjects
o MULTIPLE TREATMENT INTERFERENCE: Results restricted to subjects who have
experienced the same treatments in the same order
If subjects are exposed to multiple treatments or performed multiple tasks
Protect: Counterbalancing, cross-over designs
o NOVELTY EFFECTS: Results restricted to new context
Effects of intervention are due to novelty/innovation
o GENERALITY ACROSS MEASURES, SETTING & TIME: Results restricted to measures,
settings & assessment conditions of the study
Effects do not transfer to other settings
Cohort effects: Group at a particular time point, can have different experiences
- External validity not important for proof of concept
- Less important than internal validity!
Chapter 3: Construct & Data Evaluation Validity
CONSTRUCT VALIDITY: Is the presumed cause the actual cause? Interpretive validity
- Confound = third variable that influences the outcome
- Threats (Table 3.1, p.73)
, o ATTENTION & CONTACT: Increase of attention for/contact with the client explains
observed effect
Protect: Control group also treatment
o SINGLE OPERATIONS/NARROW STIMULUS SAMPLING: Features that are thought to be
irrelevant (set of stimuli or experimenter) could cause the observed effect
Protect: More than 1 stimulus, experimenter, etc.
o EXPERIMENTER EXPECTANCIES: Expectancies of the experimenter influence their
behavior which in turn influences the subjects’ responses and so cause the observed
effect
Protect: Experimenters blinded; provide all experimenters with standard
statement of expectations; measure their expectations with a questionnaire &
correlate results with outcome
o DEMAND CHARACTERISTICS: Secondary incidental cues of the experiment can promote
certain behavior of the subjects and so cause the observed effect
E.g. information conveyed to prospective subjects, instructions, procedures
Protect (Table 3.2, p.81):
Post experimental inquiry: ask for ideas about purpose of the study in
the end If ideas in line with expectations = problem
Pre-inquiry: tell subjects about procedures and see how they would
perform If performance in line with expectations = problem
Simulators: Subject act like they already received procedures & try to
deceive experimenters If able to deceive (experimenters think they
actually received the treatment) = problem
DATA EVALUATION VALIDITY: Do the data & analyses demonstrate what is stated?
- Concepts (Table 3.3, p.84):
o ALPHA: Type I error, false negative, rejecting null-hypothesis when true
o BETA: Type II error, false positive, accepting null-hypothesis when false
o POWER: 1- beta, true negative, rejecting null-hypothesis when false
o EFFECT SIZE: Difference between conditions
o STANDARD DEVIATION: Variability about a mean
- Threats (Table 3.4, p.86)
o LOW POWER: = harder to detect differences
Protect: Larger sample size & effect size; Compute power in advance
o SUBJECT HETEROGENEIETY: Increased variability harder to detect differences
Protect:
Specify characteristics, inclusion & exclusion criteria for subjects
Statistically evaluate characteristics that may have an effect
o VARIABILITY IN PROCEDURES: Inconsistent procedures increase variability
Protect:
Explicit & standardized procedures
Train all experimenters together
Encourage experimenters to report when they deviate
o UNRELIABILITY OF MEASURES: Errors in measurement increase variability
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