Lecture 14

# Lecture 14 - C Multiple time series design 1 O1 O2 O3 O4 X...

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Comm. 88 Lecture 14 November 18, 2008 I. Quasi-Experimental Designs A. Time Series Designs 1. Track many observations over time , before and after a manipulation. B. Single-group interrupted time series design 1. O1 O2 O3 O4 X O5 O6 O7 O8 (group 1) 2. Pretests, then manipulation, then posttests a. Improves the “one-group pretest-posttest” b. Example: Crime prevention program Crimes Reported Jan. X Feb. 3. If you do multiple pretests and posttest you will be able to see that the crime prevention program is already going down as the months pass, and the program has no effect on the amount of crime. 4. Advantage to time series: solves some threats to internal validity (testing, maturation). a. You will be able to see a problem and fix it for the next time. b. Variation: take treatment away and then measure again i.e. if the program is actually working in preventing crime then you should close them down and see if crime goes back up.

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Unformatted text preview: C. Multiple time series design 1. O1 O2 O3 O4 X O5 O6 O7 O8 (group1) 2. O1 O2 O3 O4 O5 O6 O7 O8 (group 2) 3. Improves “non-equiv control group” design a. Example: Media Literacy Program Media Literacy Scores X A B 1 2 3 4 5 6 7 8 observations b. Variation: give comparison group treatment and keep measuring. Example Study RQ: What are the effects of listening to music (while studying) on learning? IV? DV? Possible experiment: X (music) O1 (test score) group 1 R (no music) O1 (test score) group 2 Type of design? True experiment (you can make a causal claim) What can you conclude? If you find that group one on average score is significantly higher than group 2, you can conclude that music helps. High internal validity but low external validity. Now, what if we want to test for effects of another IV? I. Factorial Design A. Purpose: 1. To examine the effects of two or more IVs simultaneously B. Factors (IVs) 1....
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