Which of the following is an agreed method of assessing the quality of conducting and reporting systematic reviews and meta-analyses?
C. Despite the increasing importance and abundance of systematic reviews and meta-analyses in the scientific literature, the reporting quality of systematic reviews varies widely. To address the issue of suboptimal reporting of meta-analyses, an international group in 1996 developed a guidance called the QUOROM Statement (QUality Of Reporting Of Meta-analyses). QUOROM focused on the standards of reporting meta-analyses of RCTs. A revision of these guidelines renamed as PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) includes several conceptual advances in the methodology of systematic reviews.
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All of the following methods are used to assess heterogeneity in a meta-analysis except:
E. Meta-analysis is generally done to combine the results of different trials, as individual clinical trials are often too small and hence underpowered to detect treatment effects reliably. Meta-analysis increases the power of statistical analysis by pooling the results of all available trials. But this comes at a small cost. Although similar studies are taken to be included in the meta-analysis, it is likely that each trial is different from each other just by chance. Sometimes the difference can occur due to foreseeable situations, e.g. the dosage of medication tested, the mean ages of the population tested, difference in the scales used, etc, may differ among studies. To measure if this heterogeneity is more than the random heterogeneity we expect, statisticians resort to certain tests of heterogeneity. They are statistical as in the chi-square test (or Q statistic), which tests the ‘null hypothesis’’ of homogeneity and the I-squared test (which measures the amount of variability due to heterogeneity). Galbraith’s plot and l’Abbé plot are pictorial representations of heterogeneity. A paired t test is generally not used to calculate the heterogeneity.
Which one of the following types of data can have potentially infinite number of values?
A. Data can be qualitative or quantitative. Quantitative data refers to measures that often have a meaningful unit of expression. This can be either discrete or continuous. A discrete measure has no other observable value between two contiguous potentially observable values, i.e. there are ‘gaps’ between values. A continuous variable, on the other hand, can take potentially infinite values. The other choices in the question refer to qualitative measures whose value can only be described and counted but cannot be expressed in meaningful units.
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A multi-centre RCT was conducted with strict inclusion criteria.
Which one of the following properties of the study is most likely to be affected by the stringent inclusion criteria?
A. A major disadvantage with RCTs is the poor generalizability of experimental findings to a clinical setting. Having strict inclusion and exclusion criteria may help chose a highly homogeneous population, increasing the internal validity of the study but at the expense of generalizability.
A researcher is interested in studying whether maternal smoking increases the risk of school refusal in children.
Which one of the following is the correct null hypothesis for the above research question?
C. In scientific research, nothing can be proven; we can only disprove presumed facts. If one wants to prove maternal smoking causes school refusal, it is best to assume that maternal smoking does not cause school refusal to start with and then proceed to disprove this statement. Such statements waiting to be disproved during the course of a research study are called the null hypotheses. The converse of the null hypothesis is called the alternative hypothesis. Research question: Does maternal smoking increase risk of school refusal? Null hypothesis: Maternal smoking does not increase risk of school refusal Alternative hypothesis: Maternal smoking increases the risk of school refusal.
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