Exam 2 Flashcards
(125 cards)
Design classification degree of experimental control
- in a true experimental design, subjects are RANDOMLY assigned to at least 2 COMPARISON groups
- experiment enables control over most threats to INTERNAL VALIDITY and provides the strongest evidence for CAUSAL relationships
- randomized control trial (RCT) is the gold standard of true experimental design
Are quasi-experimental designs true experiments?
- NO
- because they lack randomization and comparison groups
Types of group assignment for design classifications
- completely randomized design
- randomized block design
- repeated-measures design
Completely randomized design group assignment
- between subject design
- subjects assigned to groups based on a randomization process
Randomized block design group assignment
- subjects classified according to an attribute (blocking variable) (i.e. males vs females)
- then randomized to treatment groups (i.e. males get control and random group as well as females)
Repeated-measures design group assignment
- within-subjects design
- subjects act as own control
Variation with number of independent variables/factors
- single-factor designs have one independent variable
- multi-factor designs have 2+ independent variables
Single-factor design (one-way design) for independent groups
- 1 independent variable is investigated
- 1 or more dependent variables
Pretest-Posttest control groups design
- RCT with 2 groups based on random assignment
- independent groups = treatment arms
- testing pre- and post-treatment
- changes in experimental group are attributable to the treatment
- establishes cause-and-effect relationship
2-group pretest-posttest design
- comparison group receives a second form of the intervention
- 2 experimental groups formed by random assignment
- control group is not feasible or ethical
- compares new treatment with standard care
- can quantify the difference between pre and post by “delta” or the change
For GroupXTime interaction
- looks at if there is any change between the time (pre vs post) and comparing the groups’ changes to each other
- can also use a 2-way mixed design
- main effects: groups, time
- interaction: groupsXtime
Multi-group pretest-posttest control group design
- multiple intervention groups
- includes a control group
- conclude that treatment 1 is better than treatment 2 or vice versa AND that it is or is not better than no treatment
Internal validity with pretest and post-test designs
- strong internal validity
- initial EQUIVALENCE of groups can be established by pretest scores (important for inferring causality)
- SELECTION BIAS controlled because of random assignments
- HISTORY, MATURATION, TESTING, INSTRUMENTATION EFFECTS SHOULD AFFECT ALL GROUPS EQUALLY
Analysis of pretest-posttest designs
- often analyzed using CHANGE scores (diff between posttest and pretest)
- also can use analysis of covariance (ANCOVA) to compare posttest scores (using pretest scores as covariates)
Posttest only control group design
- same as pretest-posttest control group design, EXCEPT NO PRE-TEST
- used when dependent variables can only be assessed following treatment (i.e. length of stay in hospital)
- used when pretest is impractical or detrimental
- is an experimental design involving randomization and comparison groups (STRONG INTERNAL VALIDITY)
- assumes groups are equivalent prior to treatment (works best with large samples to increase probability of equivalency)
Multi-factor design for independent groups
- single factor designs have 1 independent variable (with 1+ levels), and do not account for interactions of severable variables
- multi-factor designs have 2+ independent variables
Factorial Design
- incorporates 2+ independent variables, with subjects randomly assigned to various combinations of levels of the two variables
- two-way (two-factor) design has 2 independent variables
- three-way (three-factor) design has 3 independent variables
Repeated measures Design
- up to now considered 2 independent GROUPS
- experimental and control groups created by RANDOM ASSIGNMENT and by BLOCKING
- can also use repeated measures design where one group of subjects is tested under ALL CONDITIONS, each subject acting as their OWN CONTROL (aka within-subject desgin)
Advantage of repeated measures design
- subject differences are controlled
- differences between experimental and control groups are nullified because no groups used
- physiological and other factors remain CONSTANT throughout experiment
- subjects acting as their own controls provides most equivalent “Comparison group” possible
Disadvantages of repeated measures designs
- LEARNING/PRACTICE effects when one person repeats measurements over and over
- CARRYOVER effects when exposed to multiple treatment conditions (must allow enough time for dissipation of previous effects)
- may NOT be TRUE EXPERIMENTS because NO RANDOMIZED COMPARISON GROUPS
- however, if they incorporate randomization of the order of repeated treatments/interventions then can be considered experiment
Single-factor designs for repeated measures
- one-way repeated measures design
- one group of subjects is exposed to all levels of one independent variable
- has element of looking like an experiment because randomized order of who gets what experiment in which order
Solution to problem of order effects
- randomize order of conditions/interventions for each subject so there is no bias in choosing order of testing
two-way design with 2 REPEATED MEASURES for multi-factor designs
- 2 repeated measures (=2 independent variables….i.e. type of lift and orthosis)
- each person exposed to 4 test conditions (2-way design…2X2 design)
Mixed Design for multi-factor repeated measures
- 2 independent variables (i.e. exercise is IND factor (experimental and contorl), and time is REPEATED factor (3 time periods during tests))
- 2 way design or 2X3 design