Cross-Sectional Time Series Designs: A General Transformation Approach.

Cross-sectional time series designs assess the generalizability of intervention effects across different units. The general transformation approach to time series analysis was proposed by Velicer and McDonald (1984) to avoid the model identification step. A general transformation matrix is employed for all analyses rather than the specific matrix associated with a particular model. This article extends the general transformation matrix approach to the analysis of multiple unit data by the development of a patterned transformation matrix. A sequence of tests of the parameters permits the assessment of between unit differences. The resulting procedure includes several alternative approaches as special cases and is easily implemented with only minor revisions in existing computer software.