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Experimental design ITS class December 2, 2004 ITS class December 2, 2004

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Quantitative research Quantify relationships between variables Measured on a sample of subjects Relationships expressed through effect statistics Correlations, relative frequencies, diff. between means Quantify relationships between variables Measured on a sample of subjects Relationships expressed through effect statistics Correlations, relative frequencies, diff. between means

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Types of Study Descriptive Measure things as they are Experimental Take measurements Try an intervention (treatment) Take measurements Descriptive Measure things as they are Experimental Take measurements Try an intervention (treatment) Take measurements

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Descriptive studies Case Case series Cross-sectional Cohort or prospective or longitudinal Case-control or retrospective Case Case series Cross-sectional Cohort or prospective or longitudinal Case-control or retrospective

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Experimental studies AKA longitudinal, repeated- measures, interventions Without a control group Time series Crossover With a control group AKA longitudinal, repeated- measures, interventions Without a control group Time series Crossover With a control group

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Control group studies Necessary if treatment effect cannot be “washed out” Random assignment: min. chance that either group is not typical of population Single-blind: subjects Double-blind: experimenter too Best studies: data analyzed blind Necessary if treatment effect cannot be “washed out” Random assignment: min. chance that either group is not typical of population Single-blind: subjects Double-blind: experimenter too Best studies: data analyzed blind

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Ethical issues Randomized controlled study may not be ethical E.g.: Heart disease study over 10 years Access to treatment Inform subjects of randomization Randomized controlled study may not be ethical E.g.: Heart disease study over 10 years Access to treatment Inform subjects of randomization

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Quality of designs Quality of evidence for causal relationships Least for case, case-series Cross-sectional, case-control Prospective Experimental best evidence Quality of evidence for causal relationships Least for case, case-series Cross-sectional, case-control Prospective Experimental best evidence

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Confounding Two variables may be related for other reasons Control for potential confounding factors Two variables may be related for other reasons Control for potential confounding factors

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Samples Generalizability Representative Safest: Random sample Balance: Stratified random (%s) Balance on pretest! Selection bias: Not representative Sources: age, socioeconomic status Self-selection into groups High compliance Generalizability Representative Safest: Random sample Balance: Stratified random (%s) Balance on pretest! Selection bias: Not representative Sources: age, socioeconomic status Self-selection into groups High compliance

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Sample size Statistical significance Big enough to be sure you will detect the smallest worthwhile effect To be sure = detect 80% of time Detect = 95% of time, expect a smaller value if there is no effect, p<0.05 Smallest worthwhile effect = Smallest to make a diff. to subjects’ lives Statistical significance Big enough to be sure you will detect the smallest worthwhile effect To be sure = detect 80% of time Detect = 95% of time, expect a smaller value if there is no effect, p<0.05 Smallest worthwhile effect = Smallest to make a diff. to subjects’ lives

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Statistical significance P-value: the probability of getting something more extreme than your result, when there is no effect in the population P-value: the probability of getting something more extreme than your result, when there is no effect in the population

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Sources esign.html: Good resource for basic stats esign.html: : Website for EASy-D: a database of evaluation of adaptive systems, also links to research-based usability guidelines esign.html: Good resource for basic stats esign.html: : Website for EASy-D: a database of evaluation of adaptive systems, also links to research-based usability guidelines

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