Dingle, P. (2011). Statin statistics: Lies and deception. Positive Health, 180, 1. Retrieved from the Walden Library databases.

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Weighing the Evidence
This chapter focuses on the different types of systematic reviews. The chapter discusses the advantages of this type of analysis and the steps for conducting a meta-analysis or metasynthesis.
Dingle, P. (2011). Statin statistics: Lies and deception. Positive Health, 180, 1.
Retrieved from the Walden Library databases.
In this article, the author outlines how misleading statistics are used to make false claims about the positive use of statin drugs in order to retain a market share of sales for pharmaceutical firms.
Katapodi, M. C., & Northouse, L. L. (2011). Comparative effectiveness research: Using systematic reviews and meta-analyses to synthesize empirical evidence. Research & Theory for Nursing Practice, 25(3), 191–209.
Retrieved from the Walden Library databases.
The authors of this article assert that more comparative effectiveness research (CER) is necessary to accommodate the elevated demand for evidence-based health care practices. The article supplies a summary of methodological issues relevant to systematic reviews and meta-analyses used in the process of CER.
Stichler, J. F. (2010). Evaluating the evidence in evidence-based design. Journal of Nursing Administration, 40(9), 348–351.
Retrieved from the Walden Library databases.
The quality of evidence used in EBP can vary considerably. This article highlights the necessity of critically appraising facility design research articles and using a hierarchical model to rate the strength of evidence.
Bernd, R., du Prel, J.-B., & Blettner, M. (2009). Study design in medical research: Part 2 of a series on the evaluation of scientific publications. Deutsches Aerzteblatt International, 106(11), 184–189. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2695375/pdf/Dtsch_Arztebl_Int-106-0184.pdf
This article provides guidance in evaluating the study design of scientific publications for reliability and credibility. The authors suggest that the most important elements to consider are the question to be answered, the study population, the unit of analysis, the type of study, the measuring technique, and the calculation of sample size.
Walden University. (n.d.a). Paper templates. Retrieved July 23, 2012, fro