SPCE 630 Exam Top Predicted 2024 Questions and Answers Latest Update

visual analysis of graphed data - is the cornerstone of and most frequently used data analysis method in SCD research, particularly for determining whether a study demonstrates experimental control. involves systematic procedures used to evaluate specific characteristics of data patterns and evaluate the presence of a functional relation. advantages of visual analysis - -can be used to evaluate data of individuals or small groups depending on the unit of analysis specified in the research question. -data are collected repeatedly, graphed as they are collected, and analyzed frequently -focuses on analysis of individual data patterns -discovery of potentially interesting findings that may not be directly related to the original research question or program objective. -graphic presentation of data permits independent analysis and interpretation of results formative visual analysis - conducted within and across conditions to identify behavior change during the course of a study. behavior change - occurs when data patterns in one condition are different from data patterns in the subsequent, adjacent condition for the same variable(s). summative visual analysis - conducted following study completion, across multiple opportunities to demonstrate behavior change to determine whether a functional relation exists between the independent variable and the dependent variable. adjacent conditions - in SCD research, data patterns are examined within and across adjacent conditions; when data in one condition differ from what is predicted based on the preceding condition, behavior change is demonstrated. formative analysis is conducted in two steps - 1. within and across adjacent condition analyses 2. systematic examination of specific data characteristics within condition visual analyses - are conducted to discern patterns within a single condition during a study. within condition visual analyses of level, trend, and variability/stability are critical for determining when to change conditions, deciding whether adaptations need to be made, and providing information related to answering research questions. beginning with the initial condition, typically baseline, you should look for stability of data across a minimum of at least three to five sessions prior to changing conditions. condition change criteria - should be made a priori based on hypothesized data patterns. these criteria will guide both formative and summative decisions about experimental control. level - refers to the amount of behavior that occurs, as indicated by the ordinate scale value. the characteristic of highest interest for behavior change, and is generally described as low, moderate, or high. trend - the slope and direction of a data series or the direction data are moving over time. three characteristics can be described: trend directions, trend magnitude, and trend stability. trend direction - referred to as accelerating, decelerating, or zero celebrating. trend can further be characterized by magnitude, and is often described as steep or gradual and paired with direction. also describe whether the direction of a trend is improving (therapeutic) or deteriorating (contra-therapeutic). contra therapeutic trend - represents a common data pattern in SCD data that might occur within a condition and particularly prior to the introduction of the independent variable. this refers to trends that are in the opposite direction of the hypothesized direction of improvement and can establish need for the intervention. variability - fluctuation from one data point to the next and is the opposite of stability; in data with no trend, this can be summarized as the range of data values within a condition or as the percentage of data points falling within a given stability envelope stability - is predictability and consistency of data values within a condition. perceptions of this can be influenced by scales and ranges of y axes.