Research methodology – 1

Published on 23/05/2015 by admin

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Last modified 23/05/2015

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53 Research methodology – 1

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1. For a skewed distribution, the median is a more useful measure of central tendency than the mean. image image
2. When comparing recovery rates between two samples, parametric statistics are best. image image
3. For two studies with identical effect sizes, the p value will be smaller for the study with much larger numbers. image image
4. If the confidence interval for the difference in Ham-D scores between treatment groups includes 0, we can conclude that it is likely that there is a real difference between treatments that is not due to chance. image image
5. A type I error means that a result is falsely found to be statistically significant. image image
6. A very low p value indicates that a result is clinically significant. image image
7. An effectiveness study for a treatment for depression is more likely to include patients with co-morbid conditions than an efficacy study. image image
8. The need for informed consent can limit the external validity of treatment studies. image image
9. A scale must have good reliability for it to have good validity. image image
10. We should assess the criterion validity of new scales that measure depressive symptoms. image image
11. Log transformation is sometimes essential before parametric statistical tests are used. image image
12. Non-parametric tests use the difference in medians and the inter-quartile range. image image
13. Not taking into account dropouts from treatment may introduce bias. image image
14. The use of intention to treat analysis may reduce accuracy of results. image image
15. Subjects in cluster randomized controlled trials (RCTs) are analysed in exactly the same way as in standard RCTs. image image
16. Crossover studies can have more power than using different patients in different treatment groups. image image
17. Stratification can be used to control for confounding in a case-control study. image image
18. The t-test is commonly used to look at strength of association in case-control studies with a dichotomous exposure of interest. image image
19. Multiple logistic regression is used to investigate the effects of variables on a continuous outcome measure. image image
20. In multiple linear regression, if two covariates are highly correlated, there may be a type II error. image image
21. Multiple linear regression cannot be used if there is a heavily skewed distribution of a proposed variable. image image
22. For a screening test for schizophrenia, sensitivity will probably be lower for a random community sample than for a psychiatric inpatient sample. image image
23. A meta-analysis will give more accurate and less biased results than one RCT.