1
Q
Measurement Systems Info
A
Some classes of a behavior lend themselves to a specific of recording; others to another
2
Q
Data
A
The material that influences and evaluates behavior analytic services
- Empirically guides you
- Quantitative results of measurement
- Raw data doesn’t tell you much, this is why ABA uses graphs
3
Q
Occurrence
A
Something that occurs, and the action or fact of happening or occurring
AKA: Repeatability; Percentage measures
4
Q
Occurrence AKAs
A
- Repeatability
- Percentage measures
5
Q
Repeatability Measures (Definition & Details)
A
Behavior that is counted
- Behavior must have a clear start and end
- Do not use for continuous behaviors with long durations
3 Types: Count; Rate; Celeration
AKAs: Countability; Occurrence; Event recording
6
Q
3 Types of Repeatability Measures
A
- Count
- Rate
- Celeration
7
Q
Repeatability Measures AKAs
A
- Countability
- Occurrence
- Event recording
8
Q
Count (Definitions & Details)
A
- The # of occurrences
- Not enough information for programming decisions
- Use when observations time is constant across observations
AKA: Frequency
9
Q
Count AKAs
A
Frequency
10
Q
Rate (Definition & Details)
A
- # of occurrences / time
- Unit of time must be standard to compare data
11
Q
Rate (Use)
A
- Use for free operant behavior
- NOT for DTT and continuous behaviors
12
Q
Celeration (Definition& Details)
A
- Changes in rate / time
- Must be a min of 7 measures
13
Q
Celeration (Use)
A
Use for examining rates of response change over time; fluency
14
Q
Percentage Facts
A
- An occurrence measurement
- Proportional quantity
- Min. 30 response opportunities
- No % over 100%
15
Q
Trials to Criterion (Definition)
A
- An occurrence measurement
- A measure of the # of response opportunities to achieve a pre-specified level of performance
16
Q
Trials to Criterion (Use)
A
- Evaluation mastery of a class of concepts
- Comparing 2 or more procedures
- Measuring skills
- Can be measured by count, rate, duration, and latency
17
Q
2 Types of Derivative Measures of Occurrence
A
- Percentage
- Trials to criterion
18
Q
Percentage Cons
A
- Assumed progress
- Doesn’t reflect fluency
- Restricts limits of data
19
Q
Temporal Dimensions of Behavior (Definition)
A
- Measure behavior using timing
- Data measures the length and/or point in time of behavior
Categories:
- Temporal extent: Duration
- Temporal locus: Latency; IRT
20
Q
Temporal Dimensions of Behavior Categories
A
Temporal extent
- Duration
Temporal locus
- Latency
- IRT
21
Q
Duration (Definition)
A
Length of time the behavior occurs from the onset to offset
2 Methods to Calculate:
- Total Duration
- Duration per Occurrence
AKA: Temporal Extent
22
Q
Duration (Use)
A
Primary time is the amount of time a client engages in a behavior; High rates of behavior
2 Methods to Calculate:
- Total Duration
- Duration per Occurrence
AKA: Temporal Extent
23
Q
2 Methods to Calculate Duration
A
Total Duration: Add up the cumulative amount of time your client engages in the response in the total session
Duration per Occurrence: Measure the duration of time that each episode of the response
24
Q
Duration AKAs
A
Temporal Extent
25
Latency (Definition)
Duration of time between the onset of a stimulus and initiation of a behavior
- Reported using means and medians of response latencies per observation period
AKA: Response latency
26
Latency (Use)
Use for when your primary concern is in the response latencies that are too long or short
AKA: Response latency
27
Interresponse Time (IRT) (Definition)
Duration of time that elapse between 2 consecutive instances of behavior
- Report as: Mean, media, and range of IRT per session
Rates of responding
- Shorter IRT = Higher rate
- Longer IRT = Lower rate
28
Interresponse Time (IRT) (Use)
When your primary concern is the time between behaviors; identifying interval criteria for DRO schedules
- Used in: DRL and DHR
Rates of responding
- Shorter IRT = Higher rate
- Longer IRT = Lower rate
29
Latency AKAs
Response latency
30
Types of Definitional Measure
- Topography
- Magnitude
31
Topography (Definition)
- Measurable and changeable dimension of behavior
- Physical form/shape of behavior
- NOT function; Different topographies can have the same function
AKA: Form
32
Topography (Use)
Measuring behaviors that require a specific form, style, physical skill to be correct and/or effective
33
Topography AKAs
Form
34
Magnitude (Use)
Use for measuring the force of a behavior when the specific intensity is needed for successful responding, severity of dangerous behaviors
AKAs: Strength; Force; Intensity; Severity
35
Magnitude AKAs
- Strength
- Force
- Intensity
- Severity
36
Direct Measure of Behavior (Definition & Use)
- Measuring behavior as it is occurring
- Use for: Free operant; Discrete; Minor displacement in space/time
37
Indirect Measures of Behavior (Definition & Use)
- When behavior can't/ isn't being measured as it is happening; Used when there are no means of getting direct access to a behavior
- Inferences are made about what occurred vs what actually occurred
- Violates the APPLIED dimension of ABA
38
Product Measures (Definition & Ways)
- Measure behavior after it has occurred by looking at changes in the environment
- Can be measured: Naturally (bylooking); Event recording; Timing; Time sampling
39
Product Measures Pros
- Freedom to do other things
- Allows data collection for inconveniently time behaviors (sleeping)
- Increasingly, correct, complete and continuous data (rewatching a video)
- Allows multiple measurers; IOA
- Can examine behaviors with multiple response classes and intricacies
- No reactivity
40
Should you use product measures? (4Qs)
1. Is real time better? If data needs to be measured immediately > No
2. Can this behavior actually be measured by product measure? If each response does not produce the same permanent produce AND other response can produce the product > No
3. Will a contrived product negatively impact the behavior? (Camera reactivity)
4. Is it costly? If it is too costly and not worth it > No
41
Time Sampling Procedures (Definition)
Direct methods to recording behaviors during intervals or at specific moments in time
3 Forms:
- Whole
- Partial
- MTS
AKAs: Interval recording; Discontinuous measurement system
42
Time Sampling Procedures (Use/Nonuse)
- Use for continuous behavior or high rate behavior
- Behavior with no clear start / end (Not discrete)
- Don't use for: Specific critical (but infrequent) behaviors
43
Whole Interval Recording (Details)
- A form of time sampling
- Record behavior during the ENTIRE interval
- Produces an estimate of total duration
- Report the % of total intervals
44
Whole Interval Recording (Use/Nonuse & Outcomes)
- Use for: When you want to increase behavior because
- Don't use for: Behaviors you want to decrease
- Underestimates the % of a behavior's occurrence
- Longer intervals are more likely to produce underestimations
45
Time Sampling AKAs
- Interval recording
- Discontinuous measurement system
46
Partial Interval Recording (Details)
- A form of time sampling
- Overestimates the % of a behavior's occurrence AND total duration
- Underestimates the rate of high-rate behaviors
47
Partial Interval Recording (Use/Nonuse & Outcomes)
- Overestimates the % of a behavior's occurrence AND total duration
- Underestimates the rate of high-rate behaviors
- More conservative; use when you want decrease a behavior
- Don't use: When the target behavior is one you want to increase
48
Momentary Time Sampling (Details)
- A form of time sampling
- Record behavior at the END of the interval ONLY
- Report the % of total intervals in which the behavior occurred
- Misses a lot of behavior
49
Momentary Time Sampling (Use/Nonuse)
Use
- When you are not able to continuously measure throughout the entire interval
- Easily identifiable behaviors
- When measuring multiple behaviors at a time
Don't use for
- You care about the behavior being accounted for
- Low count and short duration
50
Planned Activity Check
A variation of MTS for groups
AKA: PLACHECK
51
3 Indicators of Trustworthy Measurement
- Validity: Data is valid when it represents the relevant dimension of the behavior
- Accuracy: Data is accurate when the observed value is the true value
- Reliability: Data is reliable when repeat measurements produce the same result
52
3 Indicators of Trustworthy Measurement (Description)
- Relative concepts that range from low to high
- Must be valid and accurate to be trustworthy
Ranging low to high
- Validity
- Accuracy
- Reliability
53
Validity (Defintion)
- An indicator of trustworthiness
- Represents the relevant dimension of the behavior
- Most important; without it accuracy and reliability are moot
- Inaccuracy makes Valid data Invalid
Threats
- Indirect measurements
- Measurement artifacts
- Measuring the wrong things
54
Validity (3 Fundamentals)
- Relevant dimension
- Directly measuring socially significant target behavior
- A guarantee that the data represents the behavior occurring in the conditions of interest
Threats
- Indirect measurements
- Measurement artifacts
- Measuring the wrong things
55
Threats to Validity
- Indirect measurements; Measure by proxy
- Measurement artifacts: Does not provide a meaningful representation of the behavior (Misleading)
- Measuring the wrong things / dimension (Most threatening to Validity)
56
Measurement Artifacts (Definition & Causes)
A threat to Validity
Does not provide a meaningful representation of the behavior (Misleading)
3 Causes
1. Discontinuous measurements - Produces over and underestimations
2. Poorly scheduled measurement periods
3. Limiting measurement scales - An artificial floor / ceiling
57
Accuracy (Not on Task List)
- An indicator of trustworthiness
- The observed value is the true value
- Helps us to identify and fix issues with IOA
- If measurement is not Valid, makes Accuracy moot
- If true values can't be established, rely on reliability
Threats
- Human error (#1 Threat to Accuracy)
- Weak measurement system
- Poor observer training
- Measurement bias
- Reactivity
58
Threats to Accuracy & Reliability
- Human error (#1 Threat to Accuracy)
- -Poorly designed measurement systems
- -Bad observer training
- -Unintended influences on observer
- Weak measurement system
- Poor observer training
- Measurement bias
- Reactivity
59
Reliability
- An indicator of trustworthiness
- Dependability of measurement
- Repeat measurements produce the same result
- Poor reliability = Problems with accuracy
- Reliable does not mean valid or accurate
Threats
- Human error
- Weak measurement system
- Poor observer training
- Measurement bias
- Reactivity
60
Threats to Reliability
Human error (#1 threat to reliability)
Weak measurement system
Poor observer training
Measurement bias
Reactivity
61
Weak Measurements Systems
Threats to Accuracy & Reliability
- The more behaviors being recorded, the worse your data
- Use simple measurement systems to reduce errors
62
Poor Observer Training
Threats to Accuracy & Reliability
- Train to a standard of established competency
- Provide ongoing training to minimize observer drift
63
Observer Drift
Threats to Accuracy & Reliability: Poor Observer Training
- When observers have a shift / drift in how they interpret the operational definition of the target
- To minimize, collect IOA
- If needed, retrain observers on the correct operational definitions
64
Measurement Bias
Threats to Accuracy & Reliability
- Nonrandom measurement error
- Measurement that is influenced by an expectation / belief that behavior will / won't occur under certain conditions
- Data that overestimates or underestimates the true value of an event
65
Observer Reactivity
When an observer's data collection is influenced by the awareness that they are being monitored and evaluated
- Can be minimized by observing unobtrusively
66
Interobserver Agreement (IOA)
- Most common mean to ensure quality of measurement
- The degree to which 2 observers report the same values
- High IOA = High believability
67
IOA (Benefits & Uses)
- Assess a new staff member's competence
- Identify observer drift
- Increases / decreases confidence that the definition and measurement code wasn't too difficult
- Supports that any data variability isn't due to who was recording, but a change in behavior
68
IOA (Information)
- Reported in a %
- Minimum of 20% of session across time
- Goal: 100% (Minimally 80%)
69
Methods for Calculating IOA
Repeatability: Total count; Mean count per interval; Exact count per interval; Trial by trial
Temporal/Duration: Total duration: Mean Duration (or IRT) per occurrence
Time Sampling: Interval by interval; Scored interval; Unscored interval
70
Total Count IOA
Method of Repeatability
How: (Total smaller count / Total larger count) * 100
- Simplest repeatability measure
- Overestimates agreement
71
Mean Count Per Interval IOA
Method of Repeatability
How: ((Int 1 Total IOA + Int 2 Total IOA + Int 3 Total IOA) /3 (# of Total Int)) * 100
- Calculates the agreement between the count within each interval
72
Exact Count Per Interval IOA
Method of Repeatability IOA
How: ((# of Int with 100% IOA) / Total # of Int) * 100
- Strictest IOA method
- % of total intervals in which both observers record the same thing
73
Trial by Trial IOA
Method of Repeatability IOA
How: ((# of trials in agreement) / Total # of trails) * 100)
- % of agreement between observers who measure occurrence or nonoccurrence of behavior
- Use for DTT
74
Total Duration IOA
Method of Temporal Measure IOA
How: (Shorter Duration / Longer Duration) * 100
- % of agreement regarding total duration
- Overestimates actual agreement
75
Mean Duration Per Occerrence
Method of Temporal Measure IOA
How: ((Dur IOA B1 + Dur IOA B2 + Dur IOA B3) /3 (# of Behaviors)) * 100
- Most precise temporal / duration IOA
76
Interval by Interval
Method of Time Sampling IOA
How: ((# of Int in agreement / Total Int) * 100 )
- # of scored and unscored Int with 100% IOA
- Likely to overestimate agreement with behaviors that occur at a very high / low rate
AKA: Point by Point IOA; Point by Point Agreement Ratio IOA
77
Interval by Interval IOA AKAs
- Point by Point IOA
- Point by Point Agreement Ratio IOA
78
Scored Interval IOA
Method of Time Sampling IOA
How: ((# of Int with agreed occurrence) / # of Int with at least 1 recorded occurrence) * 100
- Use for behaviors that typically occur approximately 30% of intervals or fewer
- Only uses intervals in which both observers scored an occurrence
- Minimizes overestimation by ignoring intervals in which measure by chance is highly likely
79
Unscored Interval IOA
Method of Time Sampling IOA
How: ((# of Int with agreed nonoccurrence) / # of Int with at least 1 recorded nonoccurrence) * 100
- Stricter for high rates of behavior
- Use for behaviors that typically occur approximately 70% of intervals or more
- Minimizes overestimation by ignoring intervals in which measure by chance is highly likely
- Only uses intervals in which both observers scored a nonoccurrence
80
Graphs
- Reveals relations between a series of measurements and relevant variables
- Visually allows you to examine quantitative info
- For organizing, storing, interpreting, and communicating results
81
5 Types of ABA graphs
Equal Interval: Line graph; Bar graph; Cumulative record; Scatter plot
Non-Equal Interval: Standard Celeration Chart
82
Equal Interval Graph (Definition)
The distance between any 2 consecutive points on both the x and y axis are always the same
- All intervals are the same size
83
Line Graphs
- Most common graph in ABA
- Based on the Cartesian plane
- Show the level of some quantifiable feature of the DV in relation the IV
- Y-axis should be shorter than the x-axis
- Maximum of 5 different data paths on 1 set of axes
84
Bar Graphs
- Use for: Group summative performance; Separate data sets that aren't related
- Don't use for: Trend; Variability
- Based on Cartesian plan
- No successive time is displayed on x-axis
85
Cumulative Record (Definition & Details)
- Skinner in EAB 1957
- Total # of behaviors since the start of data collection
- Behavior is only recorded once per observation period
- Steeper slope = Faster rate of responding
- Gradual slope = Slower rate of responding
86
2 Types of Cumulative Record Response Rates
- Overall response rate = An average rate of response over a given time period
- Local response rate = An average rate of response during periods of time smaller than that for which an overall response rate has been given
87
Scatter Plot
- Illustrates the relative distribution of each measurement
- Unconnected data points; Different symbols representing specific times
- Use for examining patterns in the temporal distribution of the behavior
AKA: Pattern Analysis
88
Scatter Plot (Pros & Cons)
Pros: Identifies time periods when the challenging behaviors occur
Cons:
- Correlational data only (No ABC)
- Only a hypothesis of function
- Subjective
- No replacement behaviors offered
89
Standard Celeration Chart
Ogden Lindsley (Precision Teaching)
90
4 Fundamental Properties of Behavior Change
- Data points
- Level
- Variability
- Trend
90
Data Point
A Fundamental Properties of Behavior Change
- More data and time = More confident measurement
- High variability needs more data points; fewer needed with less variability
91
Level
A Fundamental Properties of Behavior Change
- A change in Level = A change in the data average
- Line is drawn at the mean or median level
- May camouflage variability
92
Variability
A Fundamental Properties of Behavior Change
- A bounce in the data
- Use to determine how steady the data is
- High variability = Low control over the elements that effect your client
93
Trend
A Fundamental Properties of Behavior Change
- Overall direction of a data path
- Direction: Increasing; Decreasing; Zero Trend
- Degree: Gradual; Steep
BEH 0003
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