Other Quasi-Experimental Designs Design Variations Show specific design fea

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Other Quasi-Experimental Designs Design Variations Show specific design fea

Bellarmine College, US has reference to this Academic Journal, Other Quasi-Experimental Designs Design Variations Show specific design features that can be used so that address specific threats or constraints in the context Proxy Pretest Design Pretest based on recollection or archived data Useful when you weren?t able so that get a pretest but wanted so that address gain N O1 X O2 N O1 O2

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Separate Pre-Post Samples Groups alongside the same subscript come from the same context. Here, N1 might be people who were in the program at Agency 1 last year, alongside those in N2 at Agency 2 last year. This is like having a proxy pretest on a different group. N1 O N1 X O N2 O N2 O Separate Pre-Post Samples Take random samples at two times of people at two nonequivalent agencies. Useful when you routinely measure alongside surveys. You can assume that the pre in addition to post samples are equivalent, but the two agencies may not be. R1 O R1 X O R2 O R2 O N N Double-Pretest Design Strong in internal validity Helps address selection-maturation How does this affect selection-testing? N O O X O N O O O

Switching Replications Strong design in consideration of both internal in addition to external validity Strong against social threats so that internal validity Strong ethically N O X O O N O O X O Nonequivalent Dependent Variables Design (NEDV) The variables have so that be similar enough that they would be affected the same way by all threats. The program has so that target one variable in addition to not the other. N O1 X O1 N O2 O2 NEDV Example Only works if we can assume that geometry scores show what would have happened so that algebra if untreated. The variable is the control. Note that there is no control group here.

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NEDV Pattern Matching Have many outcome variables. Have theory that tells how affected (from most so that least) each variable will be by the program. Match observed gains alongside predicted ones. If match, what does it mean? NEDV Pattern Matching A ?ladder? graph. What are the threats? r = .997 NEDV Pattern Matching Single group design, but could be used alongside multiple groups (could even be coupled alongside experimental design). Can measure left in addition to right on different scales (e.g., right could be t-values). How do we get the expectations?

Regression Point Displacement (RPD) Intervene in a single site Have many nonequivalent control sites Good design in consideration of community-based evaluation N(n=1) O X O N O O RPD Example Comprehensive community-based AIDS education Intervene in one community (e.g., county) Have 29 other communities (e.g., counties) in state as controls measure is annual HIV positive rate by county RPD Example 0 1 0 . 0 8 0 . 0 7 0 . 0 6 0 . 0 5 0 . 0 4 0 . 0 3 0 . 0 7 0 . 0 6 0 . 0 5 0 . 0 4 0 . 0 3 X Y

RPD Example 0 1 0 . 0 8 0 . 0 7 0 . 0 6 0 . 0 5 0 . 0 4 0 . 0 3 0 . 0 7 0 . 0 6 0 . 0 5 0 . 0 4 0 . 0 3 X Y Regression line RPD Example 0 1 0 . 0 8 0 . 0 7 0 . 0 6 0 . 0 5 0 . 0 4 0 . 0 3 0 . 0 7 0 . 0 6 0 . 0 5 0 . 0 4 0 . 0 3 X Y Regression line Treated community point RPD Example 0 1 0 . 0 8 0 . 0 7 0 . 0 6 0 . 0 5 0 . 0 4 0 . 0 3 0 . 0 7 0 . 0 6 0 . 0 5 0 . 0 4 0 . 0 3 X Y Regression pine Treated community point Posttest displacement

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