Intervention Analysis with Control Groups
Copyright policy )Intervention Analysis with Control Groups
Summary: Control groups may be used in situations where there are time series observations. However, there appears to be no systematic treatment of the statistical issues in the literature. Structural time series models are formulated in terms of unobserved components, such as trends and seasonals, which have a direct interpretation, and multivariate structural time series models are shown to provide an ideal framework for carrying out intervention analysis with control groups. They also facilitate analysis of the potential gains from using control groups and the conditions under which single equation estimation is valid.
longitudinal data, control groups, structural time series models, Applications of statistics, co-integration, common trends, unobserved components, Time series, auto-correlation, regression, etc. in statistics (GARCH), dummy variables, seat belts, time series
longitudinal data, control groups, structural time series models, Applications of statistics, co-integration, common trends, unobserved components, Time series, auto-correlation, regression, etc. in statistics (GARCH), dummy variables, seat belts, time series
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