Determine the overall outcome of a functional relationship in 5 single-subject designed research studies through visual analysis of graphed data
STEP 1: Review this basic definition and rationale
RATIONALE: For you to be able to critically analyze the overall outcomes of a SSED behavior change research study, it is important for you to be able to answer the bottom-line question “Did this intervention result in a positive outcome?”: to answer this question: It’s essential to be able conduct a visual analysis of graphed data with regard to:
• Level
• Trend
• Variability/stability
• Latency of change
• Nonoverlapping data
In short, visual analysis entails visual inspection of graphed data for the degree of level, trend, and variability of data within and between experimental conditions
STEP 2: Watch these video on visual analysis, and then answer the 5 questions that follow:
Video 1: Single subject design visual analysis
Question 1: One way to identify a difference across baseline and intervention conditions/phase is by looking at (select all that apply):
a) The level of the independent variable
b) The level of the dependent variable
c) The mean of the independent variable
d) Examining how the level in each phases differs
Question 2: When we are looking at how the data change in direction each time within each phase, we are looking at:
a) Variability
b) Level
c) Trend
d) Mean values
Question 3: One way to determine a difference (that is a functional relationship) across conditions is to:
a) See different/opposite trends across conditions in the independent variable
b) See trends going in the same direction across conditions independent variable
c) See different/opposite trends across conditions in the dependent variable
d) See trends going in the same direction across conditions dependent variable
Question 4: Variability/stability refers to:
a) The average/mean level of data across phases
b) The change in the direction of the data across phases
c) Changes in the level within a phase
: Visual analysis that provides evidence of a strong unambiguous change (and a functional relationship between the independent and dependent variable) indicating a positive outcome has the following data patterns:
a) Changes across conditions in level, trend, and variability
b) Delayed latency of change in intervention condition
c) Highly variable overlapping data across conditions
d) Trends in the desired direction in baseline