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Do they differ and do they predict 1-year outcomes? Kahler, C. Journal of Consulting and Clinical Psychology, vol. Keene, J. A qualitative study of two agencies, in International Journal of Drug Policy, vol. Kelly, J. Prevalence, predictors, and counteracting treatment influences, in Journal of Substance Abuse Treatment, vol. A multivariate process model of effects, in Journal of Studies on Alcohol, vol. Kingree, J. Kurtz, L. Levine, B.

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Preliminary results, in Journal of Psychoactive Drugs, vol. Longabaugh, R. Mengis, M. Moos, R. Connections between participation in professional treatment and Alcoholics Anonymous, in Journal datinb Substance Abuse Treatment, vol. Morgenstern, J. Ouimette, P. A comparison of treatment effectiveness, in Journal of Consulting and Clinical Psychology, vol. Examining mechanisms underlying patient-treatment matching hypotheses for step and cognitive-behavioral treatments for substance abuse: Alcoholism, in Clinical and Experimental Research, vol.

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Stephenson, G. A linguistic analysis of diary entries, in Addictive Behaviors, vol. Swora, M. Tavares Rodrigues, J. An analysis of twelve steps programming of Alcoholics Anonymous, in Psicologia em Estudo, vol. Thevos, A.

Treatment comparisons, in Research on Social Work Practice, vol. Timko, C. One-year outcomes, in Drug and Alcohol Dahing, vol. Tonigan, J. Villanueva, M. Significao, M. Group Analysis, vol. Wilson, K. Winters, K. Witbrodt, J. The advantage of IDs, is that jamovi does not need to maintain a list of levels internally, which can improve performance when interacting with very large data sets. When starting with a blank spreadsheet and typing values in, the data and measure types will change automatically depending on the data you enter. This is a good way to get a feel for which variable types go with which sorts of data.

Similarly, when opening a data file, jamovi will infer the variable type from the data in each column. In both cases, this automatic approach may not be correct, and it may be necessary to manually specify the data and measure type with the variable editor.

The variable editor allows you to change the name eignificato the variable, and for data variables the data type, the measure type, the order of the levels, and the label displayed for each level. The variable editor can be dismissed by significafo the close arrow, slgnificato by pressing F3 again. Computed Variables Computed Variables are those which take their value by performing a computation on other Variables. Computed Variables can be used for a range of purposes, including log transforms, z-scores, sum-scores, negative scoring and means. This will produce a formula box where you can specify the formula.

The usual arithmetic operators are available. Some examples of formulas are: There are many more functions available. V-functions A number of functions appear in pairs, one prefixed with a V and the other not. V functions perform their calculation on a variable as a whole, where as non-V functions perform their calculation row by row.

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