Identifying the Precise Statistical Software Used in Studies
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A primary reason to be concerned about identifying the precise statistical software used in studies is that different software packages can produce varying results, owing to differences in the estimation methods and algorithms used to perform specific statistical analysis. (Dembe et al, 2011). Public health practice relies on the peer-reviewed public health literature for current research and findings that support an evidence basis for effective practice. Studies have shown that statistical literacy and knowledge are needed for understanding published research. The rapid growth and widespread availability in computing power and user-friendly statistical software packages in recent decades have led to the use of more advanced statistical methods and analyses being used and reported in the health literature. The most common statistical software package cited as used by most study authors was the SAS Software System.
Most public health studies show that descriptive statistics were reported in a tabular or graphical format in more than 95% of the articles. Somewhat surprisingly, when statistical techniques were used, classical statistical modeling techniques were infrequently used, with logistic regression as the most commonly reported type of model applied in the articles(Hayat et al, 2017). When statistical techniques were used, the vast majority of statistical methods seen in sample studies were classical statistical techniques commonly taught in a first or second course in introductory and intermediate statistics. Classical statistics is based on normal theory and rooted in the general linear model (GLM), a framework that includes the three t-tests, linear regression, and ANOVA. The GLM paradigm assumes independence between observations. When this assumption is violated, as is the case with repeated measures data, more advanced statistical techniques are needed to account for the data dependencies that arise. Advanced statistical modeling techniques, including mixed and marginal models, are such methods. However, these techniques, as well as complex statistical modeling techniques such as structural equation modeling and factor analysis, were rarely applied and reported in public health studies (Hayat et al, 2017).
Reference
Dembe, A. E., Partridge, J. S., & Geist, L. C. (2011). Statistical software applications used in health services research: analysis of published studies in the U.S. BMC health services research. 11. pp 252. https://doi.org/10.1186/1472-6963-11-252
Hayat, M. J., Powell, A., Johnson, T., & Cadwell, B. L. (2017). Statistical methods used in the public health literature and implications for the training of public health professionals. PloS one. 12(6). e0179032. https://doi.org/10.1371/journal.pone.0179032
Respond to the bold paragraph ABOVE by using one of the option below… in APA format with At least two references and a minimum of 200 words….. .(The List of References should not be older than 2016 and should not be included in the word count.)
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