Research Methods Unit 3 Flashcards
Single-Factor multi-level design
A design with one independent variable, which has three or more levels
What are the two advatnages of a single factor multi-level design
- Allows for a non-linear interpretation (ex: time as an iv is non-linear while drug dose is linear)
- Allows the experimentors to ask more questions/ have multiple research hypothesis ( one per level)
Why is the Bradford and Johnson study important?
It is an example of a mutli-level experiment design with linear categorization. (and though each level there can be alternate examples that can be disproven with the data if the design is tight)
Discrete variable
Variables that are isolated from one another (there is no middle ground between the points)
- use a bar graph to represent these points
Continuious variable
A variable that is connected with the other data points and exist on a continious scale
- works best with a line graph
Yoked control group
A control group where the control and experimental groups do everything the same expect for one thing. (the manipulation)
Example of a yoked control group
In the rat sleep deprivation study the rats enact the same beahvior because they are on the same spinning platform and therfore must output the same amount of exercise otherwise one will fall in the water. This is used to maintain equivalency between groups. (the only difference here being the sleep deprived/ hypervigalent rat vs the non-sleep deprived rat)
What makes up a factorial design?
- The design allows for many questions to be answered
- Designed to study the interactions between the independent variables
- Must have at leas two independent variables
How do you decipher factorial notation?
- Dertimine number of factors by counting how many values there are
- The number of levels is the number written for each variable
- Number of conditions is defined by multiplying the numbers together
What comprises an Independent group factorial design?
- 2 or more indepedent variables
- All variables are between subject
- all variables are manipulated
- all participant groups are equal
- All participant groups are randomly assigned
What comprises a matched group factorial design?
- Has 2 or more independent variables
- All indepdent variables are between subjects
- all indepdent variables are mainpulated
- all participant groups are equal
- all participant groups are matched
What comprises an ex post facto factorial design ?
- Has two more more indepdent variables
- All independent variables are between subject
- All indepdent variables are subject variables]
- all participant groups are not equal
- The groups are potnetially matched for equivalency
What comprises a repeted measures factorial design?
- Has 2 or more independent variables
- All independent variables are within subject
- all independent variables are manipulated
- All participant groups are either tested once (w/ complete or partial counterbalencing) or more than once with (reverse or blocking counterbalencing)
What comprises a mixed factorial design?
- 2 or more independent variables
- at least one within and one between subject variable
- All indepdent variables are manipulated
What comprises a mixed PxE factorial design?
- 2 or more independent variables
- One between and one within subject indepdent subject
- One manipulated and one subject variable
What comprises a PxE factorial design ?
- 2 or more independent variables
- All between subject design
- At least one manipulated at least one subject
What is an interaction effect?
When the effect of an indepdent variable is dependent on the level of another indepdent variable (interested in the interaction between the two)
What is a main effect?
The question posed about a specific independent variable (how one of the independent variables in a design shakes out in the experiment= 1 effect not impacted by the others at play in synthesization)
What is scenerio 1
Scenerio 1 details factor A having a main effect but not the B factor or an interaction. effect.
ex: recall is better using imagry but is unaffected but is unaffected by presentation rate.
- First gather the data
- then fine your inner punnet square averages
- fine the row or collum means
- plot on a graph the inner averages for all values
- should show that factor A is the ideal outcome
(remember any difference is a significant difference)
What is scenerio 2?
Where factor B has a main effect but factor A does not, nor is there a interaction effect
ex: recall is better with slower rates of presentation but imagry training was not effective in improving recall.
-Where factor B has a main effect but factor A does not, nor is there a interaction effect
First gather the data
- then fine your inner punnet square averages
- fine the row or collum means
- plot on a graph the inner averages for all values
- should show that factor B is the ideal outcome
What is scenerio 3?
When both factors A and B have main effects but there is no interaction effect
ex: recall rate is better with slower rates of presentation plus the imagry instructions where effective in improving recall
First gather the data
- then fine your inner punnet square averages
- fine the row or collum means
- plot on a graph the inner averages for all values
- Shows that the two independent variables are corellated but no interaction is present in the numerical data
What is scenerio 4?
Where both factor A and B have main effects and there is an interaction effect between the two.
ex: Overall imagry instructions are more effective in improving recall regardless of presentation rate. Bt slow presentation rate yielded dramatic improvement for the rote repetition.
First gather the data
- then fine your inner punnet square averages
- fine the row or collum means
- plot on a graph the inner averages for all values
- There should the indication of an intersection point on the graph
What is a causal relationship?
A relationship between two variables where one causes the other
What is a correlational relationship?
The compartive relationship between two variables
(correlation does not imply causality)
