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PSY 311 Ch. 11
Book notes
| Question | Answer |
|---|---|
| The variable that differentiates the groups of participants or the groups of scores in nonexperimental and quasi-experimental is called | quasi-independent variable |
| Factor | an independent variable in an experiment, especially those that include two or more independent variables |
| Factorial Design | a research design that includes 2 or more factors |
| Two-Factor Design | a research study involving 2 independent or quasi-independent variables |
| Single-Factor Design | a research study with one independent variable or 1 quasi-independent variable |
| How many separate groups of participants would be needed for a between-subjects, two-factor study with 3 levels of factor A and 4 level of factor B? | 12 |
| The primary advantage of a factorial design is that it | allows researchers to examine how unique combinations of factors acting together influence behavior |
| Main Effect | in a factorial study, the mean differences among the levels of one factor |
| Interaction between factors | whenever one factor modifies the effects of a second factor or depend on the different levels of a second-factor |
| If the mean differences between the treatment conditions are explained by the main effects, | then the factors are independent and there is no interactions |
| When the effects of one factor depend on different levels of a second factor, indicated by existence of converging or crossing lines in a graph | interaction |
| To identify an interaction, you must | compare the mean differences in any individual row with the mean differences in other rows |
| If the size and direction of the differences in one row are the same as the corresponding differences in other rows--> | no interaction |
| In general, the presence of an interaction can | obscure or distort the main effects of either factor |
| The two-factor study allows researchers to evaluate 3 separate sets of mean differences: | 1. the mean difference from the main effect of factor A 2. the mean difference from the main effect of factor B 3. the mean difference from the interaction between factors -are separate and completely independent |
| Which of the following is not a possible outcome from a 2 x 2 factorial design? | All the above are possible outcomes---> 2 main effects and an interaction, 2 main effects, and no interaction, no main effect for either factor but an interaction |
| Disadvantage of Between-Subjects Design | require a large number of participants and individual differences can become confounding variables and increase the variance of the scores |
| Advantage of Between-Subjects Design | completely avoids any problem from order effects because each score is completely independent of every other score |
| Disadvantage of Within-Subjects Design | number of different treatment conditions that each participant must undergo, time-consuming, increase the potential for testing effects (ex: fatigue) and make it more difficult to counterbalance the design to control for order effects |
| 2 Advantages of Within-Subjects Design | require only one group of participants and eliminate or greatly reduce the problems associated with individual differences |
| Within-Subjects Designs are best suited for in which | individual differences are large, and little reason to expect order effects to be large and disruptive |
| Between-Subjects Designs are best suited in which | a lot of participants are available, individual differences are relatively order effects are likely |
| Mixed Design | combines 2 different research designs. A common example with one between-subjects factor and one within-subjects factor |
| Combined Strategy | combines two different research strategies such as experimental and nonexperimental or quasi-experimental, in the same factorial design |
| Combined strategy involves one factor that is a true independent variable consisting of a set of manipulated treatment conditions, and a second factor that is a quasi-independent variable that falls into one of the following categories: | 1. second factor is a preexisting participant characteristic 2. second factor is time |
| Pretest-posttest nonequivalent control group design: | involves two separate groups of participants. One group-the treatment group-is measured before and after receiving a treatment. Second group-the control group- measured twice but does not receive any treatment between the two measurements |
| In a Pretest-posttest nonequivalent control group design the O represents | an observation or measurement X: indicates a treatment -Each row corresponds to the series of events for one group |
| Higher-Order Factorial Design | with more than two factors |
| A two-way interaction such as A x B indicates that the | effect of factor A depends on the levels of factor B |
| A three-way interaction such as A x B x C indicates that the | two-way interaction between A and B depends on the levels of factor C. |
| The two-factor ANOVA conducts 3 separate hypothesis test: | one each to evaluate the two main effects and one to evaluate the interaction |
| A factorial study measures allergy symptoms before and after taking meds. for a group taking the real medication and a control group taking a placebo. What kind of design is being used? | Mixed design |
| Which of the following accurately describes a two-factor analysis of variance? | it conducts 3 separate hypothesis test and produces 3 F-ratios |
| Limiting generalization reduces the | external validity of the study |
| By using the order of treatments as a second factor, it is possible to evaluate ay order effects that exist in the data, 3 possible outcomes: | 1. No order effects 2. Symmetrical order effects 3. Nonsymmetrical order effects |
| Symmetrical order effects | when order effects exist, the scores in the second treatment are influenced by participation in the first treatment |
| Nonsymmetrical order effects | produce a lopsided or nonsymmetrical, interaction between treatments and orders |
| How can variance be reduced in a between-subjects design? | counterbalance and use a factorial design with the order of treatments as a second factor |
| How can order effects be measured and evaluated? | counterbalance and use a factorial design with the order of treatments as a second factor |
| which of the following is a possible use for a factorial design? | Replicate and expand previous research -Examine order effects for a within-subjects study -Reduce variance in a between-subject study |
| Factorial designs examine influence of multiple independent variables | independently (main effect) -in combination (interactions) |
| On a graph bar, if bars are the same height, then there is | no main effect |
| On a bar graph, if two bars are different heights, then there is | a main effect |
| In a 2 x 2 design, the amount of numbers= | the numbers of independent variables |
| In 2 x 2 design, each number= | how many groups (levels) in each independent variable |
| You have a main effect if an independent variable has the same effect in | all conditions of the other independent variable |
| Interaction effect | when the effect of one independent variable depends on group (condition) of the other -you have an interaction if one independent variable has a different effect in different conditions |
| Two types of interactions | 1. Cross-over interactions 2. Ordinal interactions |
| Cross-over interactions | when independent variable has opposite effect in one condition of the second independent variable than the other |
| Ordinal interactions | when independent variable has a stronger effect in one condition of the second independent variable than the other |
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