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PSYC300 Research Methods For the Behavioral Sciences Textbook Notes (Dr. Charles Stangor)Chapter 11: Experimental Research: Factorial Designs- Factorial experimental designs- experimental designs with more than one independent (manipulated) variable o Factor- each of the manipulated independent variableso Two way design with two levels of each facto, 2x2 (since there are two numerals, there are two factors and each factor has two levels 2x3 has two factors, one which has two levels and the other has 3 levelso The total number of conditions (cells) can be found through manipulation of the number of levels in each factor Ex: 2x2 has 4 conditions, 3x3 has 9 conditions, 2x4x2 has 16 conditions- Two-way Designo In many cases, factorial designs involve the addition of new independent variablesto one-way experiments, often with the goal of finding out whether the original results will hold up in new situations Ex: Children who have viewed violent cartoons subsequently play more aggressively than those who have viewed nonviolent cartoonsgoal is to test whether the relationship between the viewing of violent cartoons and aggression will hold up in all situations or whether the pattern might be different for children who have previously been frustratedo Manipulate two factors in the same experiment Ex: - First factor- type of cartoons viewed, violent vs. nonviolent (same as in one-way)- Second variable- state of the children before viewing cartoons, frustrated vs. non-frustrated o Crossing the factors- conditions are arranged such that each level of each independent variable occurs with each level of the other independent variables Crossing 2 factors, each with 2 levels, results in 4 different conditions- Ex: 1- violent cartoons-frustrated 2- violent cartoons-nonfrustrated 3- nonviolent cartoons-frustrated 4- nonviolent cartoons-nonfrustrated- 2x2 design (cartoon type: violent, nonviolent x prior state: frustrated, not frustrated)o Schematic diagram- specific predictions of the research hypothesis are noted Greater than (>) and less than (<) signs areused to show the expectedrelative values of themeans - Main effectso Marginal means- The means of thedependent variable within the levels of any one factor,which are combined across the levels of one or more other factors in the designo Main effect- differences on the dependent measure across the levels of any one factor, controlling for all other factors in theexperiment - Interactions and Simple Effectso Factorial designs make predictions about interactions between or among the factorsViolent NonviolentFrustratedPriorState: Not FrustratedCartoon TypeDV: Aggressive PlayViolent NonviolentFrustratedPriorState: Not FrustratedCartoon TypeDV: Aggressive Play2.68 3.255.62 2.172.973.904.152.71Condition means (2.68, 3.25,5.62, 2.17)Marginal means (children who viewed violent cartoons behaved significantly more aggressively (M=4.15) than those who viewed nonviolentcartoons (M=2.71))Main effect (children who had been frustrated (M=2.97)behaved somewhat less aggressively than children who had not been frustratedo Interaction- pattern of means that may occur in a factorial experimental design when the influence of one independent variable on the dependent variable is different at different levels of another independent variable(s)o Simple Effect- the effect of one factor within a level of another factor Ex: Effect of viewing violent vs. nonviolent cartoons for frustrated kidso It is often useful to visualize the relationships among the variables using a line charto Crossover interaction- when the interaction is such that the simple effect in one level of the second variable is opposite, rather than just different, from the simple effect in the other level of the second variable- Three-way design- three independent variables, each of which has two levelso 2x2x2 (cartoon viewed: violent, non-violent x prior state: frustrated, not frustratedx sex of child: male, female)o Increased number of means, main effects, and interactionso Three-way interaction tests whether all three variables simultaneously influence the dependent measure Null hypothesis is that the two-way interactions are the same at the different levels of the third variable- Mixed factorial designs- designs in which some factors are between participants and some are repeated measures- Means comparisons- conducted to discover which group means are significantly different from each other0123456Non-Violent Viol entAggressive PlayCartoonNFFAggressive PlayCartoonNFF0123456Non-Violent ViolentNFFAggressive PlayCartoon00.511.522.533.5Non-Violent Viol entNFFShows the actual pattern found; research hypothesis is supported because the predictedcrossover interaction is observed, but there is also an unanticipated main effect of the cartoon factor (mean in violent cartoon condition is greater thanthe mean in the nonviolent Shows a main effect of the prior state variable only (demonstrates frustrated children were more aggressive than non-frustrated children)Shows there is only a main effect, but no interaction (the children showed more aggression after viewing violent cartoons regardless of whether they were frustrated.- Pairwise comparisons- most common type of mean comparison in which any one condition mean is compared with any other condition mean- Experimentwise alpha- probability of the experimenter having made a type 1 error in at least one of the comparisonso Planned comparisons (a priori comparisons)- can reduce experimentwise alphaby comparing only the means in which specific differences were predicted by the research hypothesiso Post hoc comparisons- when specific comparisons have not been planned ahead of time, increases in experimentwise alpha can be reduced by this approach In some cases only allow researchers to conduct them if the F test is significanto Complex comparisons- two or more means are compared at the same time to deal with increases in experimentwise alpha Usually conducted with contrast


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UMD PSYC 300 - Chapter 11: Experimental Research

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