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Enhancing Awareness on Statistical Issues in Research Articles

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11 diapositives · 149 Views · Jan 06, 2020

Explore the frequency of errors in statistical methods, the essence of statistical significance, and the need for clearer study design and methodology in research articles. Learn to assess crucial study components and avoid biases in data collection and analysis.

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  1. Statistical Issues

  2. Statement of the Problem • How often are articles published with errors in statistical methods? • So what? Should we believe only articles with perfect methodology? • What is “statistical significance”? • Why is the definition given a “modest statement”?

  3. Background • Why don’t authors refine their methods until they’ve removed the role of chance? Then we could forget statistics altogether. We’d like to be certain that our therapies work, that we only apply them when necessary, and that they are not harmful. • The last sentence of the first full paragraph on page 550 implies that—even if the studies are well designed and analyzed—1 in every 20 articles reports incorrect results. Can’t we be sure? Isn’t there a better way?

  4. 5 Parts • What are the 5 parts of a “well-designed study”? • How do you read a study and decide whether each of these parts have been adequately met?

  5. Intro • In a paper’s Introduction section, what do you look for? • In the “review of the literature,” what do you look for? • No study is comprehensive. How do you assess whether the “statement of purpose” of this paper is clear, relevant and potentially useful? • How do you assess if the paper has a “clear concept about the specific hypothesis to be tested”?

  6. Methods-Participants • In a paper’s Methodology section, what do you look for? Most methods sections begin with a description of the study participants. How do you assess each of the following? • Was the study population representative of some typical group? • What forms of bias may be acting in the selection of the study population? • What forms of bias were enacted by the inclusion/exclusion criteria? • How do assess whether these study participants are representative of the population of interest?

  7. Methods-Study Design • Most methods sections include a discussion of the study design. Designs usually include comparison groups. Why? Consider the following: • What was the control group (what did this control for? And not control for?) • What was the positive intervention tested in the study? • Exactly how are the participants assigned to the study groups? (randomly?) • How do we assess possible biases in group membership?

  8. Methods-Measurement • All methods sections include discussion of what was measured and how.Is the description of how and what was measured sufficient? • Is the measurement process reproducible? • Who was blind to the experimental groups: Those measuring? Those applying the intervention? The study participants? Exactly when was the data unblinded? • If evaluations are subject to interpretation, are assessments by more than one blinded evaluator made?

  9. Measurement-issues not addressed in Baumgardner • Are multiple units measured within an individual?That is, in dentistry it is possible to have “split-mouth” designs, to measure multiple quadrants, to measure multiple teeth, to measure multiple sites within teeth, to have multiple sections (layers) of tissue.How are these multiple measures handled? • Does an individual receive one and only one intervention or multiple interventions? • Additionally, some studies measure characteristics over time (on multiple occasions). Thus, each individual can act as its own control. However, these multiple time-points must be taken into account in the analyses.

  10. Table II