Measurement, Data Display, and Interpretation
Domain C asks how behavior is defined, measured, checked and graphed, and how graphs are read. Expect calculations (rate, agreement), choices between measurement methods, and questions about what a data pattern means.
Defining and measuring behavior
Measurement starts with an operational definition that names observable topography. The outline distinguishes direct, indirect and product measures and asks you to measure occurrence and temporal dimensions. The dimension you measure should be the one that matters to the question being asked.
Continuous and discontinuous measurement
Continuous methods capture every instance; discontinuous methods sample. Knowing the direction of each sampling method's error is more useful than memorizing a rule of thumb. The right choice depends on the dimension of interest and on what the observer can realistically do.
Quality of measurement
Validity asks whether the right dimension of the right behavior is measured; accuracy asks whether values match the true values; reliability asks whether the measure gives the same value for the same behavior. Interobserver agreement supports believability but does not establish accuracy or validity. Procedural integrity applies the same measurement logic to the people delivering the intervention.
Displaying and interpreting data
Line graphs show change over time, bar graphs summarize discrete categories, and cumulative records show rate as slope. Visual analysis looks at level, trend and variability within and across phases. Decisions are made on the pattern of data, not on a single data point.
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