MOST practice decision-making
Example 2: Smoking cessation
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If you are interested in practicing fitting the ANOVA models, constructing interaction plots, and deciding which components to include in the hypothetical intervention, follow steps 1 – 6 of the instructions below.
If you are interested only in practicing the decision-making process, skip steps 1 – 4, and begin on step 5.
Instructions
- Read the description of the experiment provided below.
- Download the artificial data set and import the data into your preferred statistical software package (e.g. SPSS, STATA).
- Estimate the ANOVA model, including main effects and interactions.
- Construct any interaction plots that may be useful in the decision-making process.
- Use the ANOVA output and relevant interaction plots to practice the decision-making process (you can use the file provided if you wish to skip steps 1—4).
- Check the answer key file to determine whether you chose one of the best combinations of components and component levels to build your hypothetical intervention.
Description of pediatric obesity example
A smoking cessation researcher is interested in developing an intervention. The researcher wishes to estimate the effects of five intervention components:
- PATCH (use of nicotine patch);
- GUM (adlib use of nicotine gum);
- PRECOUN (in-person precessation counseling before the quit date);
- CESSCOUN (in-person cessation counseling for two weeks after the quit date);
- PHONE (phone counseling during weeks 3—6).
The researcher decides to use a 25 factorial design for the experiment, N=512. The first four factors correspond to the first four components. Each has 2 levels: yes (included in the intervention package, coded 1 in the data set) and no (not included, coded -1 in the data set). The 5th factor corresponds to PHONE, and has the following 2 levels: intensive (weekly counseling, coded 1 in the data set), and minimal (a single session, coded -1 in the data set). The outcome variable is a scale measuring the participant’s beliefs about their ability to quit smoking; a higher score indicates more self-efficacy.