Missing time-series data and the impact of sentencing guidelines in Minnesota: can the debate be adjudicated?

Article Abstract:

The issues raised by Stewart J. D'Alessio and Lisa Stolzenberg and by Carlisle Moody and Thomas Marvell pertain to the effect of missing data in measuring the impact of an innovation and how these may be handled. Both the methods used and recommended are flawed in that neither Moody and Marvell nor D'Alessio and Stolzenberg considered the issue of statistical power of a time series evaluation design. The power is optimized when the number of pre- and post intervention observations are equal. A more definite conclusion regarding the impact of the Minnesota intervention needs an augmented data base aside from the time series data.

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The uncertain timing of innovations in time series: Minnesota sentencing guidelines and jail sentences - a comment

Article Abstract:

Stewart J. D'Alessio and Lisa Stolzenberg measured the effects of the sentencing guidelines and jail sentences innovations using an autoregressive integrated moving average analysis. However, their exclusion of 22 months of data prior to and four months of data immediately following the application of the innovation makes the findings spurious. One way to solve the problem of pinpointing with as much accuracy as possible when an innovation begins to take effect is by treating observations surrounding the innovation as missing data. Selection of which data to exclude must be done cautiously and must be justified.

Methods, Evaluation, Evaluation research (Social action programs)

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Challenges for multilevel models of school disorder: response to Hoffmann and Johnson

Article Abstract:

The authors discuss individual-based variables as greater predictors of school misconduct than local- or community-based variables. Earlier criticism of their multilevel modeling called into question their use of a small sample size of schools. The authors refute this critism pointing out the importance of sampling individuals within the schools, and lending less credence to between-school effects on the concluding data.

United States, Students, Crime, School violence, Juvenile delinquency

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