Solution Focused Therapy
Application Assignment 2.1: Time Series Designs
Introduction
Time series analysis is a statistical research approach appropriate for an important class of longitudinal research designs. Time series designs typically involve single subjects or research units that are measured repeatedly at regular intervals over a large number of observations. Time series analysis is a great example of a longitudinal design. A time series analysis can help us to identify the pattern of change in a behavior over time or evaluate the effects of either a planned or unplanned intervention.
Intervention Model
There is yet to be one time series model that is claimed to be the best. One design model that is often used in a school setting is an intervention model. This model involves the analysis of the effects of an intervention that is applied to an individual subject or unit (Crosbie, 1993). This model is commonly referred to as an “interrupted time series analysis”. Repeated measurements are taken before and after the intervention in order to provide a sufficient number of data points to conduct a statistical analysis to evaluate the effects of the intervention. Such investigations can be very useful in trying to understand the process and result of the intervention. One drawback of this model is the generalization of the effects on an intervention for a large population since investigations are usually conducted on single subjects (Crosbie, 1993).
Multiple Baseline Model Another commonly used model of time series analysis is a multiple baseline model. This model involves the measurement of multiple people both before and after a planned intervention. This model has several advantages over the intervention model which only measures a single case. In a multiple baseline model, the start of an intervention is staggered. This assures that the changes in behavior are due to the intervention rather than an outside factor. By gathering
Introduction
Time series analysis is a statistical research approach appropriate for an important class of longitudinal research designs. Time series designs typically involve single subjects or research units that are measured repeatedly at regular intervals over a large number of observations. Time series analysis is a great example of a longitudinal design. A time series analysis can help us to identify the pattern of change in a behavior over time or evaluate the effects of either a planned or unplanned intervention.
Intervention Model
There is yet to be one time series model that is claimed to be the best. One design model that is often used in a school setting is an intervention model. This model involves the analysis of the effects of an intervention that is applied to an individual subject or unit (Crosbie, 1993). This model is commonly referred to as an “interrupted time series analysis”. Repeated measurements are taken before and after the intervention in order to provide a sufficient number of data points to conduct a statistical analysis to evaluate the effects of the intervention. Such investigations can be very useful in trying to understand the process and result of the intervention. One drawback of this model is the generalization of the effects on an intervention for a large population since investigations are usually conducted on single subjects (Crosbie, 1993).
Multiple Baseline Model Another commonly used model of time series analysis is a multiple baseline model. This model involves the measurement of multiple people both before and after a planned intervention. This model has several advantages over the intervention model which only measures a single case. In a multiple baseline model, the start of an intervention is staggered. This assures that the changes in behavior are due to the intervention rather than an outside factor. By gathering
References: Sheperis, C.J., Daniels, M.H., & Young, J.S. (2009). Counseling Research: Quantitative, Qualitative and Mixed Methods. Upper Saddle River, New Jersey: Pearson. McCleary, R., & Hay, R.A., Jr. (1980). Applied time series analysis for the social sciences. Beverly Hills, CA: Sage. Crosbie, J. (1993). Interrupted time-series analysis with brief single-subject data. Journal of Consulting and Clinical Psychology, 61, 966-974. Cuvo, A.J. (1979). Multiple-baseline design in instructional research: pitfalls of measurement and procedural advantages. American Journal of Mental Deficiency, 84 (3), 219-228.