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Experimental Design Flashcards

1
Q

Experimental Control

A

When a predictable change in behavior DV can be reliably produced by the systematic manipulation of aspect in environment

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2
Q

Behavior is

A

Individual
Continous
Determined-by functional relations
Extrinsic-variable

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3
Q

6 Components of Experiments in ABA

A 
At least one SUBJECT
At least one BEHAVIOR
At least one SETTING
At least one TREATMENT
A measurement SYSTEM
An EXPERIMENTAL DESIGN
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4
Q

Experimental Design

A

Brief but specific statement of what researchers want to learn from conducting experiments

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5
Q

At least one SUBJECT

A

ABA uses single-subject designs

Single subject acts as control

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6
Q

At least one BEHAVIOR

A

Some have more than one DV
Multiple DV can show data patterns serving as controls to evaluate and replicate effects on IV
Assess presents of IV’s effect on behaviors

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7
Q

At least one SETTING

A

Control 2 sets of environment variables to demonstrate experimental control; IV and extraneous variables
Hard to control environment in natural settings

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8
Q

At least one TREATMENT

A

Particular aspect of the environment which is manipulates to find affects on behavior

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9
Q

AKA for At least one SUBJECT

A

Single Case Design
Within Subject Design
Intra Subject Design

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10
Q

AKA for At least one BEHAVIOR

A

DV

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11
Q

AKA for At least one TREATMENT

A

IV
Intervention
Experimental Variable

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12
Q

A Measurement System and Ongoing Analysis of Data

A

Observation and recording procedures must be conducted standardized
Must detect changes in level, trend, and variability

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13
Q

An Experimental Design

A

The particular arrangement of conditions in a study so that a meaningful comparison of effects of presence, absence or different values of the IV can be made

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14
Q

2 Types of Experimental Design

A

Nonparametric Analysis

Parametric Analysis

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15
Q

Nonparametric Analysis

A

IV either present or absent during study

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16
Q

Parametric Analysis

A

Value of IV is manipulated. Seeks to discover for the differential effects of a range of values

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17
Q

Treatment Package

A

When multiple IV’s are bundled into one program such as a token economy plus praises plus time-out

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18
Q

Component Analysis

A

Looks for effect of each part of the treatment package

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19
Q

Steady State Responding

A

A pattern of responding that exhibits very little variation in its measured dimensional quantities over a period of time

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20
Q

Baseline Logic

A

Refers to experimental reasoning inherent in single-subject experimental designs
P- Prediction
V- Verification
R- Replication

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21
Q

Steady State Strategy

A

Repeated exposures of a given subject to a condition while trying to eliminate extraneous influences on behavior by obtaining a stable pattern of responding before introducing the next condition

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22
Q

Function of Baseline Data

A

Control Condition

Does not imply the absence of intervention

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23
Q

4 Patterns of Baseline Data

A 
DAVS
Descending
Ascending
Variable
Stable
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24
Q

Descending Baseline

A

Shows behaviors is already changing

Generally should not implement IV when baseline is descending unless you want behavior to increase

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25
Ascending Baseline
Shows behavior is changing | Should not implement IV when baselines is ascending unless you want the behavior to decrease
26
Variable Baseline
No clear trend | Wait it out because its due to change in environment
27
Stable Baseline
No evidence of ascend or descend trend | Best way to look at effects of IV on DV
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3 Parts of Baseline Logic
PVR Prediction Verification Replication
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Prediction
Anticipate outcome of unknown measurement Data should be collected until stability is clear More points better
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Verification
A previously predicted level of baseline responding by termination or withdrawal of the treatment variable
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Replication
Is the essence of believability Shows reliability Replication accomplished by reintroducing the IV
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5 Main Experimental Designs
``` MCRAW Multiple Baseline Changing Criterion Reversal Alternating Treatments Withdrawal ```
33
Multiple Baseline
Most widely used Flexible Staggered implementation of the intervention in a step-wise fashion across behaviors, settings, and subjects Use when reversing is unethical
34
PVR in Multiple Baseline
A functional relation requires a change in behavior with the onset of the intervention Apply IV to Bx1 when you can predict Bx will stay the same If Bx 1 and 2 remain unchanged this verifies If do change then its been replicated Most commonly 3-5 tiers
35
Multiple Baseline Across Bx
Two or more Bx of same subject After steady baseline IV is applied When steady state of responding to IV is reached then IV is applied to the next Bx
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Multiple Baseline Across Settings
Single Bx two or more settings Steady baseline- IV applied to first setting When steady response then IV is applied to next setting
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Multiple Baseline Across Subjects
One target Bx for two or more subjects in the same setting Steady baseline- IV applied to first subject When steady response IV is applied to next subject
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2 Variations of Multiple Baseline
Multiple Probe Design Delayed Multiple Baseline Inherently weaker
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Multiple Probe Design
Analyze relations b/w IV and acquisition skill sequence | Instead of baselines, probes provide basis for determining behavior change has occurred before intervention
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Delayed Multiple Design
Initial baseline and intervention begin and following baselines are added or delayed Effective when reversal design is not possible, limited resources, new behavior, subject or setting Shorter baselines do not show interdependence of DV's
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Guide for Multiple Baseline Design
Select independent similar baselines Select concurrent and related multiple baselines Do not apply IV to next behavior too soon Vary significantly lengths of baselines Intervene on the most stable baseline first
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Advantages of Multiple Baseline Design
Successful intervention do not have to be removed Evaluates generalization Easy to implement
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Disadvantages of Multiple Baseline Design
Functional relationship is not shown Effectiveness of IV is demonstrated but information regarding function of Bx IV may be delayed for certain Bx, settings, subjects Takes resources
44
Changing Criterion Design
Experimental design where initial baseline is followed by; Series of treatment phases consisting of gradually changing criteria for reinforcement or punishment Only one Bx Bx needs to be in subjects rep. Evaluates step like treatment applied gradually Technically variation of multiple baseline
45
PVR for Changing Criterion Design
Graphs in changing criterion should have lines separating a lot to show a functional relationship Experimental control is evidenced by extent the level of responding changes to conform to each new criterion If data do not fall around lines- little control The greater vertical distance between lines the more control
46
Guidelines for Changing Criterion Design
Length of phases Magnitude of criterion changes Number of criterion changes The more criterion changes the better proof of experimental control
47
Advantages for Changing Criterion Design
Does not require reversal | Enables experimental analysis within context
48
Disadvantages for Changing Criterion Design
Target Bx must already be in rep Not appropriate for analyzing effects of a shaping program No comparison design
49
Reversal Design
An experimental design in which the responding is reversed to level obtained in previous condition IV is withdrawn or reversed Alternation between baseline and particular intervention Each reversal strengthens experimental control
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3 Consecutive Phases of Reversal Design
Initial Baseline A Intervention B Return the Baseline A
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PVR in Reversal Design
Involves PVR IV is responsible for behavior change if repetition of baseline and treatment approximate the original phases Solid points- actual measure Open points- predicted data Data in shade box- verifies prediction Data in cross hatched box- data replicates
52
5 Variations of ABAB Design
``` Repeated Reversals BAB Reversals Multiple Treatment Design NCR Reversal Technique DRO/DRI/DRA Reversal Technique ```
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Repeated Reversals
Simple extension of ABAB | More reversals the stronger evidence
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BAB Reversals
``` 3 Phases IV IV removed IV reintroduced No baseline Best design when client displays severe behaviors ```
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Sequence Effects
Effects on a subjects behavior in a given condition that are the result of the subjects experience with prior condition
56
Multiple Treatment Reversal
A type of reversal design that compares two or more IV's compared to baseline and/or to each other Can cause sequence effects
57
NCR Reversal Technique
An experimental technique for showing the effects of reinforcement by using NCR as a control instead of baseline Reinforcement presented of fixed or variable schedule
58
DRO/DRI/DRA Reversal Technique
Showing effects of reinforcement by DRO, DRA,DRI as a control DRO- Following any behavior other than target DRI- Any behavior incompatible DRA- Any alternative behavior
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Irreversibility
The level of behavior observed in an earlier phase that cannot reproduced even though experimental conditions are the same as they were.
60
Alternating Treatments Design
A design in which 2 or more conditions are presented in rapidly alternating succession independent of the level of responding and effects on Bx Compares to IV's to one another Based on SD
61
AKA's for Alternating Treatments Design
``` SCAMMM Simultaneous Treatment Design Concurrent Schedules Design Alternating Treatments Design Multi-Element Baseline Design Multi-Element Design Multiple Schedules Design ```
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PVR in Alternating Treatments Design
Inspection of differences between data paths Functional relation shown when one data point is higher than another and no overlapping Degree of differential effects produced by 2 treatments determined by vertical distance between data paths Each point plays all three roles of PVR
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3 Variations of Alternating Treatments Design
Single Phase w/o Baseline With Baseline With Baseline and Final Best Treatment Phase
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Problems Avoided by Alternating Treatments Design
``` Irreversibility Sequence Effects Unstable Data No treatment withdrawal Can begin immediately ```
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Disadvantages of Alternating Treatments Design
Multiple treatment interference Limited capacity Treatments should be different
66
Withdrawal Design
Synonymous with reversal design
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2 Types of Validity
Internal | External
68
Internal Validity
The extent to which an experiments show changes in behavior are a function of the IV and not uncontrolled variables
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4 Confounding Threats to Internal Validity
Measurement Confounds IV Confounds Subject Confounds Setting Confounds
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Measurement Confounds
``` Number and intricacy of behaviors targeting May occur due to; Observer drift Reactivity Observer bias ```
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IV Confounds
IV's are complicated | Can reduce by placebo or double blind control
72
Subject Confounds
Maturation
73
Setting Confounds
Studies in natural settings are prone to confounding | Bootleg reinforcement can occur
74
Confounding Variables
Uncontrolled factor known or suspected to exert influence on the DV
75
Extraneous Variables
An aspect of ENVIRONMENT that must be held constant to prevent unplanned environmental variation
76
External Validity
Study's results are generalizable to other subjects, settings, and or behaviors Functional relation discovered should hold under different conditions Replication established external validity
77
Treatment Integrity
IV is implemented and carried out as planned
78
2 Types of Errors Evaluating ABA Research
Type I- False Positive Type II- False Negative Visual analysis used in ABA tends to lead more to Type II errors

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