Assignment: Two-Way ANOVA

Two-way ANOVA enables researchers to study the effects of a variable upon two independent variables at multiple levels. Researchers might wish to compare the exercise habits (represented by number of steps taken per month) of individuals, based on their gender and education. Two categories of gender and three education levels may be assessed. Two-way ANOVA can account for the effects of these groups, independently, on the number of steps taken each month. It can also help to determine whether interaction exists.

For this Assignment, you use two-way ANOVA with interaction. Be sure to complete all of the parts of the assignment listed below. As this is an ANOVA, you also use multiple comparisons to determine for which factors the differences are significant. Also, to avoid additional type 1 errors, you must use Tukey, one of a number of possible methods to adjust for your multiple comparisons.

The Assignment

1. Provide numeric descriptive statistics (include skewness and kurtosis if appropriate) and graphic descriptions for Sex, Educ, and Exercise. (10 points)
2. Create histograms of the number of steps (Exercise) (dependent variable) for each combination of levels for the two independent variables. Describe the data and shape of the distributions. (20 points)
3. Discuss whether the assumptions of homogeneity of variance of the groups and normality of the data on Exercise are met. Be sure to include output to support your decision on whether the assumptions have been met. (Continue with the analyses even if assumptions are not met.) (20 points)
4. Conduct two-way ANOVA with interaction and post hoc analysis (as appropriate) using Tukey to correct for multiple comparisons. Provide relevant SPSS output. (40 points)
5. Interpret the analysis results in the context of the research question: Is there a difference in the level of exercise based on a person’s sex and level of education? Include important statistics from your analysis results to support your conclusion and generalize your results, if appropriate, to the relevant population(s). (10 points)

Learning Resources

REQUIRED READINGS

Daniel, W. W. & Cross, C. L. (2019). Biostatistics: A foundation for analysis in the health sciences (11th ed.). Wiley.

• Chapter 8, “Analysis of Variance” (pp. 267-350)

For the Discussion:

Abedini, M. R., Bijari, B., Miri, Z., Shakhs Emampour, F., & Abbasi, A. (2020). The quality of life of the patients with diabetes type 2 using EQ-5D-5?L in Birjand. Health and Quality of Life Outcomes, 18(1), 18. https://doi-org.ezp.waldenulibrary.org/10.1186/s12955-020-1277-8

de Gouveia Belinelo, P., Nielsen, A., Goddard, B., Platt, L., Da Silva Sena, C. R., Robinson, P. D., Whitehead, B., Hilton, J., Gulliver, T., Roddick, L., Pearce, K., Murphy, V. E., Gibson, P. G., Collison, A., & Mattes, J. (2020). Clinical and lung function outcomes in a cohort of children with severe asthma. BMC Pulmonary Medicine, 20(1), 66. https://doi-org.ezp.waldenulibrary.org/10.1186/s12890-020-1101-6

Pettorruso, M., d’Andrea, G., Martinotti, G., Cocciolillo, F., Miuli, A., Di Muzio, I., Collevecchio, R., Verrastro, V., De-Giorgio, F., Janiri, L., di Giannantonio, M., Di Giuda, D., & Camardese, G. (2020). Hopelessness, dissociative symptoms, and suicide risk in major depressive disorder: Clinical and biological correlates. Brain Sciences, 10(8). https://doi-org.ezp.waldenulibrary.org/10.3390/brainsci10080519