Principles Of Experimental Design 2

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Variable

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any factor or attribute that can assume two or more values

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qualitative variables

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properties that differ in type

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quantitative variables

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properties that differ in amount

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discrete variables

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between any two adjacent values, no intermediate values are possible

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continuous variables

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in principle, between any two adjacent scale values, further intermediate values are still possible

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independent variable

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the presumed causal factor in a cause effect relation between two variables; in an experiment, it is a factor that the researcher manipulates, or systematically varies

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dependent variable

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the presumed effect in a cause effect relation between two variables; in an experiment, it is the behavior or outcome that the researcher measures to determine whether the independent variable has produced an effect

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situational variable

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a characteristic that differ across environments or stimuli

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subject variable

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a personal characteristic that differs across individuals

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mediator variable

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a variable that provides a causal link in the sequence between an independent variable and a dependent variable

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moderator variable

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a factor that alters the strength or direction of the relation between an independent and dependent variable

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operational definition

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defining a variable in terms of the procedures used to measure or manipulate it

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measurement

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the process of systematically assigning values (numbers, labels, or other symbols) to represent attributes of organisms, objects, or events

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scales of measurement

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rules for assigning scale values to measurements

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nominal scale

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scale values represent only qualitative differences (i.e., Differences of type rather than the amount) of the attribute of interest

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ordinal scale

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different scale values represent relative differences in the amount of some attribute

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interval scale

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when equal distances between values on the scale reflects equal differences in the amount of the attribute being measured

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ratio scale

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equal distances between values on this scale reflect equal differences in the amount of the attribute being measured and the scale also has a true zero point

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accuracy

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the degree to which the measure yields results that agreed with a known standard

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systematic error

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constant amount of error that occurs with each measurement

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reliability

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measure refers to the consistency of measurement

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random measurement

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Random fluctuations in the measuring situation that caused the obtained scores to deviate from the true score

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test-retest reliability

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determined by administering the same measure to the same participants on two or more occasions under equivalent test conditions

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internal-consistency reliability

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the consistency of a measure within itself

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validity

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does a measure actually assess what it is claimed to assess

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face validity

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concerns the degree to which the items on the measure appeared to be reasonable

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content validity

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the degree to which the items on a measure adequately represent the entire range or set of items that could have been appropriately included

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criterion validity

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the ability of a measure to predict an outcome

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construct validity

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when they measure truly assesses the construct that it is claimed to assess

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Experimental control

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the ability to manipulate independent variables, choose the types of dependent variables that will be measured, and regulate other aspects of the research environment

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confounding variable

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a factor that covaries with the independent variable in such a way that we can no longer determine which one has caused the changes in the dependent variable

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between-subjects design

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different participants are assigned to each of the conditions in the experiment

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random assignment

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a procedure in which each participant has an equal probability of being assigned to any one of the conditions in the experiment

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within-subjects design

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each participant engages in every condition of the experiment one or more times

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counterbalancing

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a procedure in which the order of conditions is varied so that no condition has an overall advantage relative to the other conditions

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single-factor design

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only one independent variable

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experimental condition

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involves exposing participants to a treatment or an "active" level of the independent variable

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control condition

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participants do not receive the treatment of interest or are exposed to a baseline level of an independent variable

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independent-groups design

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Participants are randomly assigned to the various conditions of the experiment

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block randomization

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we conduct a single round of all the conditions, then another round, then another, for as many rounds as needed to complete the experiment. Within each round, the order of conditions is randomly determined

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matching variable

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characteristic on which we match sets of individuals as closely as possible

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matched-groups design

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each set of participants that has been matched on one or more attributes is randomly assigned the various conditions of the experiment

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subject variable

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a personal characteristic on which individuals vary from one another

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natural-groups design

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a researcher measures a subject variable, forms different groups based on people's level of that variable, and then measures how the different groups respond on other variables

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order effects

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occur when participants' responses are affected by the order of conditions

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progressive effects

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reflect changes in participants' responses that result from their cumulative exposure to prior conditions

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carryover effects

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occur when participants' responses in one condition are uniquely influenced by the particular condition or conditions that preceded it

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all-possible-orders design

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the conditions of an independent variable are arranged in every possible sequence, and an equal number of participants are assigned to each sequence

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Latin Square

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an n (number of positions in the series) x n (number of orders) matrix in which each condition will appear only once in each column and each role

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random-selected-orders design

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from the entire set of all possible orders, a subset of orders is randomly selected and each order is administered to one participant

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block-randomization design

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Every participant is exposed to multiple blocks of trials, with each block for each participant containing a newly randomized order of all the conditions

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reverse-counterbalancing design

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each participant receives a random order of all the conditions, and then receives them again in the reverse order

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Factorial design

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includes two or more independent variables and crosses (i.e., combines) every level of each independent variable with every level of all the other independent variables

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between-subjects factorial design

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A factorial design in which each subject engages in only one condition

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within-subjects factorial design

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A factorial design in which each subject engages in every condition

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mixed-factorial design

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A factorial design that includes at least one between-subjects variable and at least one within-subjects variable

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Main effect

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Occurs when an independent variable has an overall effect on the dependent variable

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interaction

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Occurs when the way in which an independent variable influences behavior differs, depending on the level of another independent variable

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person X situation factorial design

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an experimental design that incorporates at least one subject variable along with at least one manipulated situational variable

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simple main effects

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the effect of one independent variable at a particular level of another independent variable

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two-way interactions

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among two independent variables, the way that one independent variable influences a dependent variable depends on the level of the second independent variable

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three-way interaction

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The interaction of two independent variables depends on the level of a third independent variable