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Epidemiology
Epidemiology and principles of research
| Question | Answer |
|---|---|
| Cross sectional Study | Finds prevalence at a point in time. Measured by Odds Ratio |
| Prevalence | Number of cases at time Y/total number of individuals at time y |
| Incidence | Number of new cases at time y/population at risk at time y |
| Incidence Density Rate | number of newly diseased individuals/sum of time periods of population at risk |
| Odds Ratio | (axd)/(bxc) Cross sectional studies -> measures prevalence, not incidence. |
| Relative Risk | (a/a+c)/(b/b+d) Cohort studies -> measures indicence |
| Incidence Rate | number of incidences/total person years |
| Cohort study | A population at risk (a cohort) is followed over time and the number that develop the disease is measured. Can be done retrospectively |
| What is the relationship between prevalence and incidence rate? | P= IR x D. D is the duration of the disease. all time units are the same. |
| What is the difference between a cohort and a cross sectional study? | A cross sectional study provides a snapshot of the prevalence of a disease at a point in time. A cohort study measures the incidence rate in the population over the time period followed |
| Rate ratio | incidence rate in the exposed/incidence rate in the unexposed. |
| Attributable Risk | Incidence rate in the exposed - incidence rate in the unexposed |
| Case control study | Compares a group with the disease to a group presumed to be disease free (not about calculating rates) |
| Case Crossover | A study where each case acts as its own control in the time before "exposure" |
| What is the gold standard of experimental study designs? | Double blind randomised controlled trial |
| A 95% confidence interval means | if we were to repeat the study many different times, then 95% of the confidence intervals calculated would include the true value, but 5% would not |
| A study finds a relative risk of 1.2 with a 95% CI of .5 - 1.6 What does this mean? | There was probably no difference in risk. Relative risk of 1.0 is no difference between the two risks. The confidence interval included this so even though the risk was 1.2 this is still a naturally occuring variation. |
| A wide 95% confidence interval means | A high rate of sampling error and low accuracy of reulst. There is a greater range between which the true value is likely to lie. |
| Standard deviations tell us what? | The variation within a group of samples. Standard deviation is the average of the differences between samples and the mean of the whole data set. |
| What is the null hypothesis? | The hypothesis that there is no difference or significant effect between the studied groups or factors |
Created by:
TurtleTurner
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