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EXPERIMENTS (Causality (Causality: change in one variable (X, IV) will…
EXPERIMENTS
Causality
- Causality: change in one variable (X, IV) will produce a change in another variable (Y, DV)
--> e.g. an increase in temperature (X) increases click-through (Y) for Molson's Coors social media ads
- Establishing causality is the main reason why we conduct experiments
--> IV responsible for change in DV
--> IV changes, DV measured against
Correlation DOES NOT EQUATE to Causation
- X and Y may be correlated bc
--> X change Y
--> Y change X
--> Z change X and Z change Y
-Z is a confound i.e. an extraneous variable that influences both X and Y
-Confound must change BOTH X and Y
3 Conditions for Causality
- X must occur before Y
- There must be an association b/w X and Y i.e. a change in X must lead to a change in Y
--> must be correlated
- There must be no other competing explanations for the r/s
--> cannot have alternative explanations for observed r/s
Validity
Internal Validity: extent to which the observed results are due to the experimental manipulation
--> low internal validity --> low external validity
Threats to Internal Validity
- History: external events that affect the responses of the ppl involved in the experiment e.g. competitor gg out of biz
- Maturation: changes in the respondents that are a consequence of time e.g. aging
- Testing: the fact that a participant has alr been previously measured may affect their future behaviour
- Instrumentation: changing measurement instrument
- Selection bias: EG (not sample) is systematically diff from population
- Mortality: respondents consistently drop out of either EG or CG while experimental research is in progress
External Validity: extent to which the observed results are likely to hold beyond the experimental setting
--> whether results will replicate in other areas, if don't have internal validity, results won't replicate in other context.
--> must have high internal to have high external
Threats to External Validity
- All threats to internal validity
- Hawthorne effect: respondents behave differently bc they know they are being observed
Ecological Validity: methods, materials and setting of the study approximate the real-world
--> isolate effects v carefully, stimuli not rich enough to capture real-world, keep everything constant
Experimental Designs
Experimental Notation
O - Any formal observation/ measurement
X - Exposure to the treatment
EG - Experimental grp
CG - Control grp
R - Random assignment
M - Matching control
Common Designs
Classical Designs
- Pre-experimental Designs:
--> one grp, after only
--> one grp, before after
--> non-matched control
--> matched control
- Quasi-experimental Designs:
--> time-series
--> continuous panel
- True Experimental Designs: (w randomisation)
--> two grp, after only
--> two grp, before after
--> solomon four grp
-
Statistical Designs
- Completely randomised
- Randomised block
- Factorial
--> to vary multiple variables simultaneously
--> allows testing of main and interaction effect (no/ +ve/ -ve synergy)
-
Lab vs Field Experiments
Lab Experiment
- Randomisation is easy and external factors can be controlled
--> high internal validity
- Subjects are in an artificial environment and aware they are being observed
--> low ecological validity
Field Experiment
- Subjects are in natural environment
--> high ecological validity
- Subjects are unaware of observation, but randomisation may be hard (e.g. price discounts in supermarkets) or easy (e.g. A/B testing)
--> high external validity?