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Main effects
difference in one factor cause difference in DV
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Interactions
- differences that may be unique from combinations of factors
- different from what would be predicted from one factor alone
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Mixed Design
included a between-subjects factor and a within-subjects factor
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nested design
- combines between and within-subjects components
- different levels of within-subjects IVs are included under each level of a between subjects factor
- used to nest tasks or groups of subjects
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pretest-posttest design
- differs from time series: single measure before and after
- true experimental design, not quasi experimental designs
- used in situations in which researcher lacks control over the assignment of participants to conditions and/or does not manipulate the caual variable of interest
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Non equivalent before-after design
used when we want to make comparisons between 2 groups that we strongly suspect may differ in important ways before the experiment begins
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longitudinal deigns
- 3 drawbacks...
- researchers typically find it difficult to obtain samples of participants who agree to be studied again and again over a long period of time
- trouble keeping track of participants: more, die
- repeated testing can lead to practice effects
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Cross-sectional designs
- cannot distinguish age-related changes from generational effects
- people of different ages differ not only in age, but also conditions under which their generation grew up
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Cohort-Sequential Design
- Disadvantage of cross-sectional and longitudinal designs is their relative inability to determine whether factors other than age are influencing observed changes
- C-S design combines two developmental designs and lets you evaluate degree of contribution made by factors such as generation effects
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Evaluating Quasi-Experimental Designs
- consider what is required to establish that a particular variable causes changes in behavior
- to infer causality, we must be able to show that: the presumed causal variable preceded the effect in time, the cause and the effect covary, all other alternative explanations of the results are eliminated through randomization or experimental control
- primary weakness: degree to which they eliminate effects of extraneous variables on the results
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