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Chapter 8

Research methods - Chapter 8 summary.pdf

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Simon Fraser University
A.George Alder

The logicof experimentation Exercisingcontrol overvariables Manipulating independent variables ▫ Experiments provide the ability to manipulate an IV, to ▫ Manipulates one IV control how and when the DV is measures, and to regulate extraneous factors ▫ Determiningthenumberof conditions → Offers best opportunity to examine how independent → Single-factordesigns  Only has one IV, must have at least two conditions variables causally influence DV  Experiment with one IV that has more than two ▫ Experimentalcontrol → Includes the ability to: conditions = single-factor, multilevel design 1. Manipulate one or more IV → IV can have two levels, but more levels are needed to determine whether the relation between an independent 2. Choose the type of DV that will be measured and dependent variable is linear or non-linear 3. Regulate other aspects of the research environment ▫ Experimentalandcontrolconditions → Experimentalcondition(group)  Exposing participants to a treatment/'active' level Causalinferenceandexperimentalcontrol ▫ Recall: 3 criteria to conclude X has causal influence on Y of IV → Control condition(group) 1. Co-variation of X and Y  Participants do not receive the treatment of → Manipulating IV interest/are exposed to a baseline level of an IV 2. Temporal order → Exposing participants to IV prior exposing to DV → In some experiments, concept of a control group does not apply 3. Absence of plausible alternative explanations → Eliminating other factors ▫ Confoundingvariable → A factor that co-varies with the IV in such a way that we Examiningtheresults:generalconcepts can no longer determine which one has caused the ▫ Most common statistical tests used to analyze data changes in DV from single-factor designs → Reduce confoundingfactors by: ▪ Keeping extraneous factors as constant as possible → t-test and analysis of variance (ANOVA)  Either test can be used if the design only across different conditions has two conditions ▪ Balancing extraneous factors that cannot be held ▫ Multilevel designs constant ▫ Potentialconfoundingvariables:environmentalfactors → ANOVA determines whether the overall pattern of difference among the mean scores → Hope to avoid systematic bias are statistically significant ▪ The experimenter consistently alters her/his  If it is significant, then post-hoc tests can behaviour toward participants based on the particular condition they are in be used to compare the means of specific conditions ▫ Potentialconfoundingvariables:participantcharacteristics → Betweensubjectsdesign ▪ Different participants are assigned to each of the conditions in the experiment ▪ Minimize confound factor by Randomassignment → A procedure in which each participant has an equal probability of being assigned to any one of the conditions in the experiment → Creating equivalent groups → Within-subjectdesign ▪ Each participant engages in every condition of the experiment one or more times ▪ Problem: fatigue → Solution: counterbalancing ▪ Procedure in which the order of conditions is varied so that no condition has an overall advantage relative to other conditions Chapter 8 Page 1 Between-subjects design Advantagesofbetween-subjectsdesign Randomassignmentvs. randomsampling ▫ No possibility of order effects ▫ Differs between each other ▫ Less likely than within-subjectsdesigns to tip off the ▫ Random sampling participants about the hypothesis/underlyingpurpose of the → Used to select the sample of individuals who will be experiment asked to participate in a particular study Disadvantagesofbetween-subjectsdesign ▫ Random assignment ▫ Less effectivethan within-subjectsdesignsin creating
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