Is there a significant difference in treatment outcome between individuals experiencing their first depressive episode and those experiencing a repeated episode? (Is episode type a significant factor in treatment outcome?)

Instruction:

1. Review the Assignment Guides, which contains tutorials on how to show the math/process work and examples of assignment answers
2. Use this Word document to fill in the answers to the questions. You must type out a clear answer to each question, even if the answer is also contained in the SPSS output.
3. Download the Excel file for this assignment and use that data set to answer all the questions in this assignment. Import the data into SPSS if instructed to do so.

Q1. Perform and Interpret a Two-Way ANOVA (17.5 points total)

The data set for Q1 has been adapted from a salary survey in a specific profession. A national sample provided demographic information and information about their employment, including annual salary. The researchers are interested in possible relationship between gender and salary, and between education and salary. In addition, they would like to know if gender and education level interact with each other in relation to salary. So instead of examining each pair of variables with a separate test, they want to perform a factorial two-way ANOVA to examine gender and education at the same time in terms of their relationships with salary. The two-way ANOVA will allow them to answer the following questions:

1. Is gender a significant factor in salary?
2. Is education a significant factor in salary?
3. Is there a significant interaction between gender and education in terms of salary?

 

1. Import data into SPSS

Import the Q1 data into SPSS and configure the variables. Take a screen shot of the variable view of the data file and paste it here to show the following:

– All variables are imported

– All variables are configured correctly in “Measure” under the “Variable View”

– The “Values” are correctly specified for all nominal or ordinal variables

(1 point: deduct .5 for each error up to 1 total)

1. Run the 2×5 two-way ANOVA with α = .05, with the additional options of descriptives and effect size estimates.

Paste the entire output for this analysis here.

If any table is missing, no point will be earned for the rest of the questions in Q1. 

1. The omnibus effect of the whole factorial ANOVA model.
2. Report the omnibus F test result in APA format including F, p, and partial h².

(2 points, deduct .5 for each error in value or format, up to 2 total.)

2. Draw a conclusion from the hypothesis testing result (reject or fail to reject the null). Explain what this omnibus test result means. (1 point: .5 for each item)
3. The main effect of Gender.
4. Report the test result on this main effect in APA format, including F, p, and partial h². (1.5 points: deduct .5 for each error in value or format up to 1.5 total.)
5. Draw a conclusion from the hypothesis testing result (reject or fail to reject the null). Explain what this test result means.

3.Create a bar graph and paste it to show the mean comparison within the main effect. Explain what the graph shows in terms of the main effect. (2 points total: see point breakdown below)

– Correct graph type (.5 point)

– Correct data (.5 point)

– Explanation of graph: Which gender tends to have higher salary than the other gender? (1 point)

1. The main effect of Education.
2. Report the test result on this main effect in APA format, including F, p, and partial h². (1.5 points: deduct .5 for each error in value or format up to 1.5 total.)
3. Draw a conclusion from the hypothesis testing result (reject or fail to reject the null). Explain what this test result means. (1 point: .5 for each item)
4. Create a bar graph and paste it to show the mean comparison within the main effect. Explain what the graph shows in terms of the main effect. (2 points total, see the breakdown below.)

– Correct graph type (.5 point)

– Correct data (.5 point)

– Explanation of graph: What is the direction of the relationship between education and salary? Where is the largest difference in salary according to the graph?  (.5 point for each question)

 

 

1. The Gender x Education interaction effect from the ANOVA.
2. Report the test result on the interaction effect in APA format including F, p, and partial h². (1.5 points: deduct .5 for each error in value or format up to 1.5 total.)
3. Draw a conclusion from the hypothesis testing result (reject or fail to reject the null). Explain what this test result means. (1 point: .5 for each item)
4. Create a line with multiple lines (Graphs-Legacy Dialogs-Line-Multiple). Enter Ed as the horizontal axis and define lines by Gender and paste it here. Explain what the graph tells us about the interaction. (2 points total, see the breakdown below.)

– Correct graph type (.5 point)

– Correct data (.5 point)

– Explanation of graph: Is the education effect on salary larger (or more dramatic) in females or in males? (1 point)

Q2. Perform and Interpret a Two-Way ANOVA (17.5 points total)

The data set for Q2 has been adapted from a study comparing two antidepressants in terms of their effect on reducing depression symptoms. There researchers would like to know which antidepressant (SSRI 1 or SSRI 2) leads to higher level of improvement for the participants. But they hypothesized that the difference between the two antidepressants may vary depending on whether the individual is experiencing their first depressive episode or repeated depressive episode. The two-way ANOVA will allow them to answer all of the following questions:

1. Is there a significant difference in treatment outcome between the two drugs? (Is drug type a significant factor in treatment outcome?)
2. Is there a significant difference in treatment outcome between individuals experiencing their first depressive episode and those experiencing a repeated episode? (Is episode type a significant factor in treatment outcome?)
3. Does the drug type effect on treatment outcome depend on whether an individual is experiencing the first episode or a repeated episode? (Is there a significant interaction between drug type and episode type in terms of treatment outcome?)

 

1. Import data into SPSS

Import the Q2 data into SPSS and configure the variables. Take a screen shot of the variable view of the data file and paste it here to show the following:

– All variables are imported

– All variables are configured correctly in “Measure” under the “Variable View”

– The “Values” are correctly specified for all nominal or ordinal variables

1. Run the 2×2 two-way ANOVA with α = .05, with the additional options of descriptives and effect size estimates.

Paste the entire output for this analysis here.

If any table is missing, no point will be earned for the rest of the questions in Q2.

1. The omnibus effect of the whole factorial ANOVA model.
2. Report the omnibus F test result in APA format including F, p, and partial h².
3. Draw a conclusion from the hypothesis testing result (reject or fail to reject the null). Explain what this omnibus test result means. (1 point: .5 for each item)
4. The main effect of Drug type.
5. Report the test result on this main effect in APA format, including F, p, and partial h². (1.5 points: deduct .5 for each error in value or format up to 1.5 total.)
6. Draw a conclusion from the hypothesis testing result (reject or fail to reject the null). Explain what this test result means.

3.Create a bar graph and paste it to show the mean comparison within the main effect. Explain what the graph shows in terms of the main effect. (2 points total: see point breakdown below)

– Correct graph type (.5 point)

– Correct data (.5 point)

– Explanation of graph: Which drug has a better treatment outcome (improvement)? (1 point)

1. The main effect of Episode type.
2. Report the test result on this main effect in APA format, including F, p, and partial h². (1.5 points: deduct .5 for each error in value or format up to 1.5 total.)
3. Draw a conclusion from the hypothesis testing result (reject or fail to reject the null). Explain what this test result means. (1 point: .5 for each item)
4. Create a bar graph and paste it to show the mean comparison within the main effect. Explain what the graph shows in terms of the main effect. (2 points total, see the breakdown below.)

– Correct graph type (.5 point)

– Correct data (.5 point)

– Explanation of graph: Which episode type has a larger improvement? (1 point)

1. The Drug x Episode interaction effect from the ANOVA.
2. Report the test result on the interaction effect in APA format including F, p, and partial h². (1.5 points: deduct .5 for each error in value or format up to 1.5 total.)
3. Draw a conclusion from the hypothesis testing result (reject or fail to reject the null). Explain what this test result means. (1 point: .5 for each item)
4. Create a line with multiple lines (Graphs-Legacy Dialogs-Line-Multiple). Enter Drug as the horizontal axis and define lines by Episode and paste it here. Explain what the graph tells us about the interaction. (2 points total, see the breakdown below.)

– Correct graph type (.5 point)

– Correct data (.5 point)

– Explanation of graph: Is the drug type difference on treatment outcome more dramatic in those with their first episode or those with their repeated episode? (1 point)