SPCE 630 LATEST 2026 TEST PAPER QUESTIONS AND
SOLUTIONS GRADED A+
✔✔between condition visual analysis - ✔✔the objective of this is to identify if behavior
change has occurred. in SCD research a particular condition (B) is introduced and re-
introduced to one (eg. A-B-A-B) or more than one (multiple baseline design) data series
to evaluate whether there is a functional relation between independent and dependent
variables.
✔✔functional relations - ✔✔are unequivocal demonstrations that an independent
variable produced reliable and consistent change in a dependent variable. the purpose
of SCD research is to determine if behavior change occurs when the intervention is
introduced, and whether the behavior change can vive reliably replicated.
✔✔analysis of data across adjacent conditions entails determining: - ✔✔a) changes in
data patterns (level, trend, variability) b) immediacy of change c) amount of overlapping
data across adjacent conditions d) consistency of data patterns across similar
conditions
✔✔immediacy of change - ✔✔across adjacent conditions is the degree to which
behavior change occurs as soon as the intervention is introduced. when a large change
in level occurs immediately after introduction of a new condition, it is referred to as an
abrupt change in level, which is indicative of an immediately powerful or immediately
effective intervention.
✔✔overlap - ✔✔refers to values of data in one condition that are in the same range of
values of data in the subsequent, adjacent condition.
✔✔consistency - ✔✔refers to the extent to which data patterns in one condition are
similar to data patterns in other conditions. confident determination that a functional
relation exists requires consistency in data patterns between iterations of the same
condition and inconsistency in data patterns between different, adjacent conditions.
✔✔potential demonstrations of effect - ✔✔a functional relation can be identified when a)
there is a sufficient number of this (three opportunities to demonstrate behavior change
contingent on condition change) and b) visual analysis suggests that consistent
changes in data occur for all potential demonstrations
✔✔the presence of a functional relation can be confirmed when - ✔✔a) there is a
successful attempt to replicate effects of a condition b) similar conditions generate
similar levels and trends within (intra participant replication) and across (inter participant
replication) participants in a study. a minimum of three demonstrations of behavior
change is required to establish experimental control
,✔✔magnitude - ✔✔if a functional relation is present, this, or amount of behavior change
may be of interest. magnitude of effect is assessed by comparing the amount and
consistency of change across conditions and cases within a study that is directly
attributed to the intervention.
✔✔systematic process for conducting visual analysis - ✔✔1. adequate number of data
points within conditions to establish data patterns.
2. clear patterns within conditions in level, trend, or stability
3. behavior change between adjacent conditions in level, trend, and/or variability
4. degree of overlap and immediacy of change in data patterns across adjacent
conditions
5. consistency of changes across conditions and cases
6. predicted patterns of change
7. magnitude of change across conditions and cases
✔✔visual analysis requires a plan - ✔✔a) deciding how often data will be graphed
b) considering how data will be graphically displayed
c) determining which data characteristics will be the focus of within and between
condition analyses
d) identifying design related criteria that will impact visual analysis
✔✔determining a schedule for graphing data, you should - ✔✔a) ensure data are
graphed regularly enough to inform decision making with respect to implementing the
design as planned and b) identify relevant threats to internal validity that can be
detected visually
✔✔identifying design related criteria - ✔✔a) minimum number of sessions per condition
and b) explicit criteria for changing conditions
✔✔summative analysis should focus on - ✔✔a) within condition data patterns were
stable b) hypothesized between condition shifts in data patterns were detected and c)
these shifts consistently co occurred with each change in condition
✔✔split middle method - ✔✔a tool that can be used to estimate trend within conditions
and compare trends between conditions.
these are most useful when within condition trends or between condition changes in
trend are of primary interest and data show moderate or high variability within
conditions.
✔✔stability envelopes - ✔✔can be used to estimate stability in level or trend within
conditions. the primary advantage of this is to ensure consistency in experimental
decisions related to data stability.
✔✔percentage of non overlapping data - ✔✔may be used to estimate level change
between two adjacent conditions. the higher the PND, the more consistent and abrupt
, the level change between adjacent conditions. a PND of 100% indicates no overlap in
the ranges of values between two adjacent conditions.
✔✔baseline logic - ✔✔serves as the foundation for all single case design research. all
SCDS are mere extensions of the basic A-B paradigms, wherein behavior is measured
repeatedly across two adjacent conditions: baseline (A) and intervention (B).
✔✔single case experimental designs - ✔✔some authors refer to designs with at least
three demonstrations of effect as this.
✔✔non experimental variations
A-B designs - ✔✔referred to s the simple time series design, represents the most basic
non experimental SCD. this design requires that the dependent variable be measured
repeatedly under controlled baseline (A) and intervention (B) conditions.
✔✔A-B-A designs - ✔✔the target behavior is repeatedly measured under baseline (A1)
and intervention (B) conditions. after the dependent variable has stabilized during
intervention, you reintroduce the baseline condition (A2) to the target behavior. this
design is susceptible to numerous threats of internal and external validity.
✔✔A-B-A-B Withdrawal design - ✔✔also referred to as reversal design, has been one
of the most frequently used SCDs in behavioral research. this design permits a clear
and convincing demonstration of experimental control because it requires the repeated
introduction and withdrawal of an intervention.
✔✔experimental - ✔✔causal attributions can be made and functional relations can be
demonstrated.
✔✔internal validity in ABAB - ✔✔maturation threats may be likely if the baseline or
intervention conditions occur for an extended period of time. control for this by using
condition lengths that are sufficient length to establish data patterns, intervening on
behaviors that are unlikely to slowly improve over time in the absence of intervention
and removing the intervention in the second baseline condition.
✔✔internval validity in ABAB - ✔✔due to the nature of withdrawal in ABAB, procedural
infidelity and carryover effects may be likely. ABAB designs are sensitive to attrition
threats in the second baseline condition when behaviors are expected to deteriorate
again.
✔✔corollary behaviors - ✔✔the concurrent monitoring of non target behaviors has
practical implications for practitioners.
✔✔advantages of ABAB design - ✔✔provides a convincing demonstration of causality
in applied research. it controls for many of the deficiencies associated with the ABA
SOLUTIONS GRADED A+
✔✔between condition visual analysis - ✔✔the objective of this is to identify if behavior
change has occurred. in SCD research a particular condition (B) is introduced and re-
introduced to one (eg. A-B-A-B) or more than one (multiple baseline design) data series
to evaluate whether there is a functional relation between independent and dependent
variables.
✔✔functional relations - ✔✔are unequivocal demonstrations that an independent
variable produced reliable and consistent change in a dependent variable. the purpose
of SCD research is to determine if behavior change occurs when the intervention is
introduced, and whether the behavior change can vive reliably replicated.
✔✔analysis of data across adjacent conditions entails determining: - ✔✔a) changes in
data patterns (level, trend, variability) b) immediacy of change c) amount of overlapping
data across adjacent conditions d) consistency of data patterns across similar
conditions
✔✔immediacy of change - ✔✔across adjacent conditions is the degree to which
behavior change occurs as soon as the intervention is introduced. when a large change
in level occurs immediately after introduction of a new condition, it is referred to as an
abrupt change in level, which is indicative of an immediately powerful or immediately
effective intervention.
✔✔overlap - ✔✔refers to values of data in one condition that are in the same range of
values of data in the subsequent, adjacent condition.
✔✔consistency - ✔✔refers to the extent to which data patterns in one condition are
similar to data patterns in other conditions. confident determination that a functional
relation exists requires consistency in data patterns between iterations of the same
condition and inconsistency in data patterns between different, adjacent conditions.
✔✔potential demonstrations of effect - ✔✔a functional relation can be identified when a)
there is a sufficient number of this (three opportunities to demonstrate behavior change
contingent on condition change) and b) visual analysis suggests that consistent
changes in data occur for all potential demonstrations
✔✔the presence of a functional relation can be confirmed when - ✔✔a) there is a
successful attempt to replicate effects of a condition b) similar conditions generate
similar levels and trends within (intra participant replication) and across (inter participant
replication) participants in a study. a minimum of three demonstrations of behavior
change is required to establish experimental control
,✔✔magnitude - ✔✔if a functional relation is present, this, or amount of behavior change
may be of interest. magnitude of effect is assessed by comparing the amount and
consistency of change across conditions and cases within a study that is directly
attributed to the intervention.
✔✔systematic process for conducting visual analysis - ✔✔1. adequate number of data
points within conditions to establish data patterns.
2. clear patterns within conditions in level, trend, or stability
3. behavior change between adjacent conditions in level, trend, and/or variability
4. degree of overlap and immediacy of change in data patterns across adjacent
conditions
5. consistency of changes across conditions and cases
6. predicted patterns of change
7. magnitude of change across conditions and cases
✔✔visual analysis requires a plan - ✔✔a) deciding how often data will be graphed
b) considering how data will be graphically displayed
c) determining which data characteristics will be the focus of within and between
condition analyses
d) identifying design related criteria that will impact visual analysis
✔✔determining a schedule for graphing data, you should - ✔✔a) ensure data are
graphed regularly enough to inform decision making with respect to implementing the
design as planned and b) identify relevant threats to internal validity that can be
detected visually
✔✔identifying design related criteria - ✔✔a) minimum number of sessions per condition
and b) explicit criteria for changing conditions
✔✔summative analysis should focus on - ✔✔a) within condition data patterns were
stable b) hypothesized between condition shifts in data patterns were detected and c)
these shifts consistently co occurred with each change in condition
✔✔split middle method - ✔✔a tool that can be used to estimate trend within conditions
and compare trends between conditions.
these are most useful when within condition trends or between condition changes in
trend are of primary interest and data show moderate or high variability within
conditions.
✔✔stability envelopes - ✔✔can be used to estimate stability in level or trend within
conditions. the primary advantage of this is to ensure consistency in experimental
decisions related to data stability.
✔✔percentage of non overlapping data - ✔✔may be used to estimate level change
between two adjacent conditions. the higher the PND, the more consistent and abrupt
, the level change between adjacent conditions. a PND of 100% indicates no overlap in
the ranges of values between two adjacent conditions.
✔✔baseline logic - ✔✔serves as the foundation for all single case design research. all
SCDS are mere extensions of the basic A-B paradigms, wherein behavior is measured
repeatedly across two adjacent conditions: baseline (A) and intervention (B).
✔✔single case experimental designs - ✔✔some authors refer to designs with at least
three demonstrations of effect as this.
✔✔non experimental variations
A-B designs - ✔✔referred to s the simple time series design, represents the most basic
non experimental SCD. this design requires that the dependent variable be measured
repeatedly under controlled baseline (A) and intervention (B) conditions.
✔✔A-B-A designs - ✔✔the target behavior is repeatedly measured under baseline (A1)
and intervention (B) conditions. after the dependent variable has stabilized during
intervention, you reintroduce the baseline condition (A2) to the target behavior. this
design is susceptible to numerous threats of internal and external validity.
✔✔A-B-A-B Withdrawal design - ✔✔also referred to as reversal design, has been one
of the most frequently used SCDs in behavioral research. this design permits a clear
and convincing demonstration of experimental control because it requires the repeated
introduction and withdrawal of an intervention.
✔✔experimental - ✔✔causal attributions can be made and functional relations can be
demonstrated.
✔✔internal validity in ABAB - ✔✔maturation threats may be likely if the baseline or
intervention conditions occur for an extended period of time. control for this by using
condition lengths that are sufficient length to establish data patterns, intervening on
behaviors that are unlikely to slowly improve over time in the absence of intervention
and removing the intervention in the second baseline condition.
✔✔internval validity in ABAB - ✔✔due to the nature of withdrawal in ABAB, procedural
infidelity and carryover effects may be likely. ABAB designs are sensitive to attrition
threats in the second baseline condition when behaviors are expected to deteriorate
again.
✔✔corollary behaviors - ✔✔the concurrent monitoring of non target behaviors has
practical implications for practitioners.
✔✔advantages of ABAB design - ✔✔provides a convincing demonstration of causality
in applied research. it controls for many of the deficiencies associated with the ABA
