Research exam 2 Flashcards
Independent Variable
- manipulated variable
- should be practical and ethical
Situational
- type of independent variable in which subjects encounter different environmental circumstances (e.g., large vs. small rooms in a crowding study)
Task
- type of independent variable in which participants are given different types of tasks to perform (e.g., mazes that differ in level of difficulty)
Instructional
type of independent variable in which participants are given different sets of instruction about to perform (e.g., given a list of stimuli, groups might be told to process them in different ways)
Experimental group
in a study with an identified control group, the experimental groups is given the treated to be tested
Control group
a group not given a treatment being evaluated in a study
- provides a means of comparison
Extraneous variable
- an uncontrolled factor not of interest to the researcher but that could affect results
- becomes a confound when it interferes with the results/performance
Dependent Variable
- behavior measured as the outcome of the experiment
- practical (measurable)
- ethical
- quantifiable (represented as a number)
- reliable (consistency, when more than one person agrees that the DV is the same)
- sensitive (should be able to detect changed from IV)
Ceiling Effect
- the level at which an independent variable no longer has an effect on a dependent variable
- the level above which variance in an independent variable is no longer measured or estimated.
Floor Effect
- statistical phenomenon in which most data points fall in the very low range of possible values (“bottom out” on the “floor” of the measure).
- often seen in assessment when a test is too challenging for a given target population.
Types of DV’s
- choice selection
- amplitude
- frequency
- speed
- latency
Amplitude (DV))
- strength of feelings (i.e., scale of 1-10)
- strongly agree/disagree, moderately agree/disagree, etc.
Frequency (DV)
how often something happens
Latency (DV)
- i.e., inverse of speed
- longer time = slower you are
Subject/person variables
- a type of independent variable that is selected rather than manipulated by the experimenter
- an existing attribute of the individuals chosen for the study (e.g., gender)
statistical conclusion validity
- the degree to which conclusions about the relationship among variables based on the data are correct or “reasonable”
Types of external validity
- population validity
- ecological validity
- temporal (i.e., other times) validity
Population Validity
- external validity
- describes how well the sample used can be extrapolated to a population as a whole
Ecological Validity
- external validity
- refers to the extent of a research study are able to generalized to real-life settings
Temporal Validity
- external validity
- whether findings from a study hold true over time
Internal Validity
degree to which an experiment is free to confounds
Threats to internal validity
- history
- maturation
- regression
- testing
- instrumentation
- subject selection
- attrition
History
- threats to internal validity
- something uncontrolled occurs DURING the course of the study that might have an impact on the behavior of the participants (i.e., fire alarm goes off during data collection)
Maturation
- threat to internal validity
- participants change in some noticeable way over the course of the study for reasons other than the research manipulation
Regression
- threat to internal validity
- participants selected on the basis of extreme scores tend to have scores that are not as extreme on a subsequent testing
Testing
- threat to internal validity
- testing participants once might change the way those participants respond if they are tested again
Instrumentation
- threat to internal validity
- something changed about the way in which data are collected over the course of the study
Subject Selection
- threat to internal validity
- participants in the different conditions are not equivalent when the study begins
Attrition
- threat to internal validity
- some participants leave the study before it’s complete
- how might this affect the comparability of the groups?
between-subjects design
- each participants is tested at one level or combination of level of the IV(s).
- Half of participants are in one group, other half are in the other group
- E.g., participants are given either no alcohol OR one 12 oz. regular beer.
Equivalent groups
Groups of participants in a between-subject design that are essentially equal in all way except levels of the independent variable
random assignment
- the most common procedure for creating equivalent groups in a between-subjects design
- each individual volunteering for the study has an equal probability of being assigned to any of the groups
matching assignment
- a procedure for creating equivalent groups in which participants are measured on some factor (a matching variable) expected to correlate with the dependent variable
- groups are then formed by randomly assigning to groups participants who score at the same level on the matching variable
Another name for within-subjects design
repeated-measures design
sequence/order effect
can occur in a within-subjects design when the experience of participating in one of the conditions of the study influences performance in subsequent conditions
carryover effect
form of order effect in which systematic changes in performance occur as a result of completing one sequence of conditions rather than a different sequence
progressive effect
in a within-subjects design, an order effect in which the accumulated effects are assumed to be the same from trial to trial (e.g., fatigue)
counterbalancing
Number of different orders of the manipulation (N!)
Ex: N= 5 → 5 x 4 x 3 x 2 x 1
Latin Square
form of partial counterbalancing in which each condition of the study occurs equally often in each sequential position and each condition precedes and follows each other condition exactly once.
Reverse Counterbalancing
- occurs in a within-subject design when participants are tested more than once per condition
- Subjects experience one sequence and then a second with the order reversed from the first (e.g., A-B-C-C-B-A)
Cross-sectional study
in developmental psychology, a design in which age is the independent variable and different groups of people are tested; each group is of a different age
Longitudinal study
in developmental psychology, a design in which age is the independent variable and the same group of people is tested repeatedly at different ages.
single-factor design
An experimental design with a single independent variable
Independent groups design
A between-subjects design that uses a manipulated independent variable and has at least two groups to which subjects are randomly assigned
matched groups design
- A between-subjects design that uses a manipulated independent variable and has at lease two groups of participants
- Subjects are matched on some variable assumed to affect the outcome before being randomly assigned to the groups
Ex post facto design
A between-subject design with at least two groups of participants that uses a subject variable or that creates nonequivalent groups
why would we use the phrase “repeated measures design”?
- In a within-subject design
- When we want to see an overall change in a person, and want to use fewer participants
Independent t-test
- Used when the two groups of participants are completely independent of each other
- Occurs whenever we use random assignment to create equivalent groups or if the being studied is a subject variable involving two different groups (i.e., male and female)
Dependent t-test
- If independent variable is a within-subject factor, or if two groups of people are formed in such a way that some relationship exists between them (e.g., participants in group A are matched on intelligence with participants in group B)
why do researchers employ multilevel designs
research designs where data for participants are organized at more than one level
continuous variable
- one for which a number of intermediate values exist – variable exists on a continuum
- Use a line graph to portray results
Discrete variable
- each level represents a distinct category and no intermediate points can occur
- Use a bar graph to portray results
When do you use an ANOVA
comparing more than two independent variables
placebo control group
led to believe that are receiving treatment when in fact they aren’t
wait-list control group
often used in research designed to assess the effectiveness of program or in studies on the effects of psychotherapy.
factorial design
Any design with 2 or more IVs being studied simultaneously
main effects
the presence or otherwise of statistically significant differences between the levels of an independent variable in a factorial design
interaction
in a factorial design, occurs when the effect of one independent variable depends on the level of another independent variable
mixed factorial design
A factorial design with at least one between-subjects factor and one within-subjects factor
P x E factorial design
p= person
- example: gender
- something you cannot manipulate
e= environment
- example: alcohol consumption - can be manipulated
ATI design
- Aptitude-Treatment Interaction
- Form of P x E factorial design found in educational research, the goal of which is to examine possible interactions between an aptitude variable (person factor) and a treatment variable (environmental factor)
