By S. Nassir Ghaemi
Obtainable and clinically suitable, A Clinician's consultant to stats and Epidemiology in psychological healthiness describes statistical strategies in undeniable English with minimum mathematical content material, making it excellent for the busy physician. utilizing transparent language in favour of advanced terminology, boundaries of statistical ideas are emphasised, in addition to the significance of interpretation - in preference to 'number-crunching' - in research. Uniquely for a textual content of this sort, there's wide insurance of causation and the conceptual, philosophical and political components concerned, with forthright dialogue of the pharmaceutical industry's position in psychiatric study. via making a higher knowing of the realm of analysis, this e-book empowers health and wellbeing execs to make their very own judgments on which statistics to think - and why.
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Extra resources for A clinician's guide to statistics and epidemiology in mental health : measuring truth and uncertainty
Not larger, and not smaller. Put another way, we don’t want a study to have unequal confounding factors in two groups despite randomizing patients to those two groups. This can happen by chance; just because we randomize, it does not follow that two groups will be equal in confounding factors. The more patients we randomize, however, the more likely that the two groups will be equal in confounding factors. The question is: how much more? The central limit theorem There are two ways to answer this question: one clinical and one mathematical.
Alvan Feinstein (Feinstein, 1977) Should we just stop using p-values? Some might think that a statistics book that makes this claim would have nothing more to say. But in fact, it should be clear by now that there is much more to statistics than p-values (or hypothesis-testing methods). In fact, statistics has little to do with p-values, or, more correctly, p-values have as much to do with statistics as alcohol has to do with sociability: too much of the former ruins the latter. Background The concept of the p-value comes from Ronald Fisher, in his work on randomization of crops for agriculture.
This obviously is nowhere near the number of repetitions that is required to equalize the two groups on most possible confounding factors. In the case of crossover studies, patients can, in a sense, serve as their own controls, as they are switched successively 24 Chapter 5: Randomization to drug versus placebo. , four patients get drug versus ﬁve patients who get placebo, without any further changes). But even with the crossover component, a study of this size is somewhat of a gloriﬁed observational study, and thus beneﬁt with the drug would only be somewhat more impressive than in an observational report.
A clinician's guide to statistics and epidemiology in mental health : measuring truth and uncertainty by S. Nassir Ghaemi