Abstract
This chapter builds on the concepts related to project design (Chap. 4) and descriptive (Chap. 5) to present a number of possible inferential statistics approaches suitable for the PIO MM (this chapter) to better understand the practical and statistical significance of the data. Interpretation of the analysis is discussed for each of the inferential methods. Selecting appropriate inferential statistics depends on your project study design, the variables representing the PIO MM concepts, and the measures used to operationalize them.
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References
Gay JM. Clinical epidemiology & evidence-based medicine glossary: experimental design and statistics terminology. Washington State University [Internet], 2010. [cited 2017 May 12] Available from: http://people.vetmed.wsu.edu/jmgay/courses/GlossExpDesign.htm
Dunn OJ, Clark VA (2009) Basic statistics: a primer for the biomedical sciences. Wiley
McDonald JH (2009) Handbook of biological statistics. Sparky House Publishing, Baltimore, MD
Engineering statistics handbook, do the observations come from a particular distribution? [Internet]. [cited 2017 May 12]. Available from: http://www.itl.nist.gov/div898/handbook/prc/section2/prc213.htm
American Psychological Association (APA) (2009) Publication manual of the American Psychological Association, 6th edn. American Psychological Association, Washington, DC
Monsen KA, Brandt JK, Brueshoff B, Chi CL, Mathiason MA, Swenson SM, Thorson DR (2017) Social determinants and health disparities associated with outcomes of women of childbearing age who receive public health nurse home visiting services. J Obstet Gynecol Neonatal Nurs 46(2):292–303
Camp RC, Tweet AG (1994) Benchmarking applied to health care. Jt Comm J Qual Improv 20(5):229–238
Monsen KA, Radosevich DM, Johnson SC, Farri O, Kerr MJ, Geppert JS (2012) Benchmark attainment by maternal and child health clients across public health nursing agencies. Public Health Nurs 29(1):11–18
Chatfield C (1995) Problem solving: a statistician’s guide. Chapman & Hall/CRC
Too big to fail: large samples and the P-value problem [Internet]. [cited 2017 May 12]. Available from: http://www.galitshmueli.com/system/files/Largesample-12-6-2012.pdf 2012
Page P (2014) Beyond statistical significance: clinical interpretation of rehabilitation research literature. Int J Sports Phys Ther 9(5):726
Greenwald AG, Gonzalez R, Harris RJ, Guthrie D (1996) Effect sizes and p-values: what should be reported and what should be replicated? Psychophysiology 3(2):175–183
Kotrlik JW, Williams HA (2003) The incorporation of effect size in information technology, learning, and performance research. Inf Technol Learn Perform 21(1):1–7
Cohen J (1992) A power primer. Psychol Bull 112(1):155–159
Johnson KE, McMorris BJ, Raynor LA, Monsen KA (2013) What big size you have. Using effect sizes to determine the impact of public health nursing inter-ventions. Appl Clin Inform 4:434–444
Monsen KA, Farri O, McNaughton DB, Savik K (2011) Problem stabilization: a metric for problem improvement in home visiting clients. Appl Clin Inform 2:437–446
Kaplan EL, Meier P (1958) Nonparametric estimation from incomplete observations. J Am Stat Assoc 53:457–481
Freedman DA (2012) Survival analysis. Am Stat:110–119
Tukey JW (1977) Exploratory data analysis. Addison-Wesley, Reading, MA
Institute for Healthcare Improvement. The science of improvement: how to improve [Internet]. [cited 2017 May 12]. Available from: http://www.ihi.org/resources/pages/howtoimprove/scienceofimprovementhowtoimprove.aspx
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Monsen, K.A. (2018). Inferential Analysis and Interpretation. In: Intervention Effectiveness Research: Quality Improvement and Program Evaluation. Springer, Cham. https://doi.org/10.1007/978-3-319-61246-1_6
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DOI: https://doi.org/10.1007/978-3-319-61246-1_6
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