The pits and falls of graphical presentation.

Graphics are powerful tools to communicate research results and to gain information from data. However, researchers should be careful when deciding which data to plot and the type of graphic to use, as well as other details. The consequence of bad decisions in these features varies from making research results unclear to distortions of these results, through the creation of "chartjunk" with useless information. This paper is not another tutorial about "good graphics" and "bad graphics". Instead, it presents guidelines for graphic presentation of research results and some uncommon, but useful examples to communicate basic and complex data types, especially multivariate model results, which are commonly presented only by tables. By the end, there are no answers here, just ideas meant to inspire others on how to create their own graphics.

Doing meta-analysis in research: a systematic approach.

Meta-analysis is an objective, systematic review that employs statistical methods to combine and summarize the results of several studies. It is a quantitative synthesis of all the unbiased evidence, meant for summarizing large volume of data, establishing and determining the magnitude of an effect, and to increase power and precision of studies. The steps to performing a meta-analysis include making a hypothesis and defining the domain of research, defining inclusion/exclusion criteria, literature search, selecting the final set of studies, extracting data on variables of interest, coding procedures, calculating effect sizes and interpretations, selecting potential moderators and examine their relationships, report writing, and critical evaluation. Meta-analysis has several strengths as well as weaknesses.

Consensus methods: a bridge between clinical reasoning and clinical research?

Evidence-Based Practice does head the "hierarchy of evidence" upon which developments in clinical practice should be based. There are, however, situations where evidence is either unavailable, unclear, or results between studies are at variance. Consensus is a reliable contingency, and approaches to reaching consensus have acceptable construct validity (Nominal Group Technique, Delphi, and Consensus Development Conference). Consensus is reached when: (i) the method of investigation tightly controls communication to reduce the obscuring "noise" of divergent discussion; (ii) statistical measures of agreement or dissent screen out the bias that would otherwise be produced by the dictate of vociferous minorities or coalitions that may represent vested interests; (iii) all participants contribute equally to the product of the investigation.