RESEARCH DESIGN Flashcards
define internal validity
the soundness of a design
how strongly we can assert the changes in out DV to the IV
define external validity
how generalisable the findings are
how representative of the world are the findings
problem associated with internal vs. external validity
ensuring internal validity = means the potentially more artificial the study becomes = less externally valid
4 steps to internal validity
sound operationalisation of DV
strong experimental design logic
sound operationalisation of IV
consideration and used of appropriate remedies to control for extraneous variables
manipulation of the IV:
define experimental manipulation
participants allocated to an IV condition by the experimenter
manipulation of the IV:
define individual differences manipulation
a characteristic of the participant determines the level of the IV which they are tested
not strictly experimental
what are the study designs
Repeated measures (within groups) - each participants tested at each level of the IV
Between groups: each participant tested at only one level of IV
Factorial: more than one IV
strengths of a factorial design
more than one IV allows for more precise hypotheses
control of extraneous variables by including as an IV
ability to determine the interactive effect of two or more independent variables
weaknesses of a factorial design
using more than two independent variables may be logistically cumbersome
higher-order interaction are difficult to interpret
what is separation and how is it achieved?
maximising the variation between groups
achieved by operationalisation of the IV
- need min. 2 IVs
- levels need to be distinctly separate
- additional intermediate levels can then be added to identify curvilinear impacts
what is compression and how is it achieved
minimising the variation within groups
achieved by controlling extraneous variables
what are the two forms of extraneous variables
noise creating
Confounding
what are noise creating variables
extraneous variable that have:
no relation to the IV
but can randomly impact the DV to create extra variation in DV
what are confounding variables?
extraneous variables that
- systematically impact the DV
- related to the IV
- potentially explain changes in DV that would be expected from the IV
how can confounds be controlled for
eliminate impact by keeping the variable constant
or building it into the study to measure its impact