M&D Unit 4

Extrinsic variability assumes behavioral variability is not: _____

Inherent to the individual

Experimentation is the basic strategy to: _____

Collect and test information

Experimental variable:

Manipulated to find effect: _____

Independent variable

Independent variable: In behavior analysis: _____

Environmental event, condition, or stimulus class

Experimental variable:

Measured & studied to see effect: _____

Dependent variable

Dependent variable: In behavior analysis: _____

Dimension of behavior or a response class

Experimental design: Specific arrangement of: _____

Environmental conditions within an experiment

Experimental control is demonstrated when behavior changes in: _____

Predictable and orderly manner

Internal validity: Extent to which: _____

DV is attributed to IV manipulation

External validity: Extent to which results are: _____

Extended to individuals, settings, or behaviors

History, maturation, testing, instrumentation, diffusion of treatment, etc.: Examples of: _____

Threats to internal validity

Threat to internal validity:

Other events or changes coincide with IV introduction: _____

History

Threat to internal validity:

Natural development or learning experiences coincide with IV: _____

Maturation

Threat to internal validity:

DV changes from repeated exposure to experimental arrangements: _____

Testing

Threat to internal validity:

Changes in data due to measurement system: _____

Instrumentation

Threat to internal validity:

Inadvertent exposure of treatment to control: _____

Diffusion of treatment

Threat to internal validity:

Changes due to baseline not representing natural state of events: _____

Regression towards the mean

Threat to internal validity:

Participant assignments may bias the outcome: _____

Selection bias

Threat to internal validity:

Loss of participants may influence effects of a study: _____

Attrition

Extraneous variables:

Unrelated events to the: _____

IV may affect the DV

Confounds: Uncontrolled variables that influence the: _____

Dependent variable

Confounds can be: _____

Known or suspected

Multiple-treatment interference: Analysis results are affected by: _____

2 or more treatments being combined

Sequence effects:

DV effects attributed to: _____

Order of experimental conditions

Carryover effects:

Behavior patterns: _____

Extend from 1 condition into a subsequent condition

Demonstrative analysis:

Seeks to determine: _____

If an intervention is effective

Parametric analysis:

Analyzes: _____

Effects of various levels of the IV

Component analysis:

Identifies: _____

Which part of a compound IV is producing behavior change

Comparative analysis:

Analyzes differential effects of: _____

2 or more IVs on the DV

Group designs:

Different individuals in the: _____

Experimental and control conditions

Single-case designs:

Individuals serve: _____

As their own control

Single-case designs:

Observed through: _____

Repeated observations over time

Baseline: _____

Measure of DV before implementing IV

Phase change: Moving from: _____

1 set of environmental conditions to another

Baseline logic compares: _____

Predicted and actual values of behavior

Baseline logic: 3 parts: _____

Prediction, verification, replication

Baseline logic helps determine: _____

Effects of the IV

A-B design: _____

1 baseline is followed by 1 intervention phase

Reversal design: _____

Baseline and experimental conditions alternate

2 variables of experimentation: _____

Independent & dependent variable

Experimental designs seek to demonstrate a: _____

Functional relation

2 types of validity in experimental design: _____

Internal and external validity

Confounds in experimental design: (3)

1. Multiple-treatment interference

2. Sequence Effects

3. Carryover Effects

Confounds in experimental design:

S _____

Sequence effects

Confounds in experimental design:

C _____

Carryover effects

Group designs:

Control is: _____

Between groups

Group designs:

IV exposure in: _____

1 condition

Group designs:

Numbers/observations: _____

Large numbers, few observations

Group designs:

Data analysis through: _____

Statistics

Group designs:

IV introduction is: _____

Randomized and matched

Group designs:

Generalization through: _____

Random selection and assignment

Single-case designs:

Control is: _____

Within individuals

Single-case designs:

IV exposure in: _____

All conditions

Single-case designs:

Numbers/observations: _____

Small numbers, many observations

Single-case designs:

Data analysis through: _____

Visual analysis

Single-case designs:

IV introduction when: _____

DV is stable

Single-case designs:

Generalization through: _____

Replication

Basis for all other experimental designs:

_____

A-B design