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Types - Broad Distinction. QualitativeQuantitative. Qualitative Research. NarrativeSubject's own wordsSummarizes behaviorsDescriptiveMethodsInterviewsObservation notesSurveys. Quantitative Research. Numerical data collected
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1. Experimental Design
2. Types - Broad Distinction Qualitative
Quantitative
3. Qualitative Research Narrative
Subject’s own words
Summarizes behaviors
Descriptive
Methods
Interviews
Observation notes
Surveys
4. Quantitative Research Numerical data collected & analyzed
Explores relationship between variables
Independent (single or multi-leveled)
Dependent (single or multiple)
Analysis may permit exploration of an interaction between variable
Experimental or quasi-experimental
5. Experimental Designs Characterized by complete random assignment of groups or subjects
Groups are independent
Usually employs strong control
6. Quasi-Experimental Designs Groups or subjects not randomly assigned
e.g., sample of convenience
May not have a comparison group
Typical of clinical research
e.g., within subjects repeated measures
Less “subject-intensive”
7. Broad Distinctions Between subjects
Dependent measures taken one time
Data are independent (i.e., not correlated)
Within subjects
A “repeated measures” design
Dependent measures taken multiple times
Data are dependent
Mixed
Between and within
8. Design Types Single factor (one-way)
Studies one independent variable
Multi-factor
Studies multiple independent variables
May have several levels
Examples:
Two-way (e.g., 2 x 2)
Three-way (e.g., 2 x 2 x 2)
Time-series
9. Single Factor Designs Pretest-posttest (one-group)
Pretest-posttest (control group)
Posttest-only (control group)
10. Pretest-Posttest (one group) Quasi-experimental
One set of measures taken before and after treatment or intervention
Compare pretest and posttest scores Analysis
paired t test
Weakness
No comparison or control group
11. Pretest-Posttest (control group) Experimental design - random assignment
Two groups
Control
Experimental
Measures on dependent variable made on both groups pre- and posttest Significant differences in experimental group not found in control group attributable to treatment
Analysis
difference scores compared with independent t test
ANCOVA pretest score as covariate
12. Multiple Factor Designs Two-way factorial
e.g., 2 x 3
Three-way factorial
e.g., 2 x 2 x 3
13. Two-Way Factorial Design Studies multiple independent variables
Main effects (ME)
Each with a number of levels (L)
Permits study of interactions
Analysis
ANOVA Example: 2 x 3
14. Three-Way Factorial Design Studies multiple independent variables
Main effects (ME)
Multiple levels (L)
Interactions effects
Analysis
ANOVA
Post hoc pairwise comparisons Example 2 x 2 x 3
15. Counterbalanced Design Possibility of order effects biasing data in a repeated measures design
Solutions
Randomize order
Counterbalance trials - order systematically varied
Example - two treatments (T1 - T2) “Crossover design”
Half of subjects - T1 then T2
Half of subjects - T2 then T1
16. Latin Square Design Minimizes order effects
17. Single Subject Design Permits analysis of effects of treatment in individual subjects (or groups)
Elements
Subjects usually own control
Repeated measures
Design phases (times series analysis)
18. Single Subject Design Time series analysis
Dependent measure is continuous
Establish baseline
Measure treatment effect over time
19. Case Report Subject a single individual
Often uses a narrative format
May be non-experimental or experimental
Develops a profile of the subject using:
Visual observation
Interviews/surveys/questionnaires
Objective data
May provide generalizations about other subjects with similar conditions