EBM Exam I

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Author:
Rx2013
ID:
132007
Filename:
EBM Exam I
Updated:
2012-02-04 17:38:22
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Biostats2
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biostats 2
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  1. power is a calculation that
    indicates whether or not a study can accurately detect statistically significant differences between samples when a difference exists
  2. simply stated, power =
    1 - beta
  3. want power to be at least
    80%
  4. a priori calculation of power
    number of subjects needed to meet power is figured out before the study is performed
  5. post hoc calculation of power
    • number of subjects needed to meet power is calculated after the study has been performed
    • potential for bias
    • could be manipulation just to get published
  6. If a statistically significant difference between groups is detected
    power is less of an issue b/c power is the chance that we will find a difference
  7. study did not enter enough pt to meet power but difference was detected?
    info we can use
  8. study had enough participants to meet power and showed a difference between groups?
    info we can use
  9. study had enough pt to meet power and showed no difference between groups
    info we canuse
  10. study did not have enough to meet power and results did not show difference between groups
    • may experience type II error
    • study did not meet power
  11. power is mentioned but without details, no % set or number of pt required to meet power
    power not met
  12. power is claimed to be met but not reported
    power not met
  13. Three types of analysis
    • per protocol
    • intent to treat
    • modified intent to treat
  14. per protocol
    number of subjects completing the trial
  15. intent to treat (ITT)
    number of subjects randomized into each group
  16. modified intent to treat
    number of subjects randomized and met pre-specified criteria (ex. 8 weeks of tx)
  17. descriptive statistics are calculated to describe characteristics of
    • a group
    • ex. patient demographics & frequency
  18. measures of central tendency
    • mean
    • median
    • mode
  19. mean
    • used on interval or ratio data
    • may be misleading on ordinal data
    • affected by outliers
  20. Median
    • used on ordinal
    • non-parametric test
  21. mode
    • variable that occurs most frequently
    • most useful with nominal data
  22. measures of variability
    • useful in measuring how close data is to the measure of central tendancy
    • range
    • interquartile range
    • variance
    • standard deviation
    • standard deviation of the mean
  23. Range
    • degree of spread
    • influenced by outliers
    • difference between largest and smallest observed
  24. interquartile range
    • used for ordinal, interval and ratio data
    • range of values remaining when the largest and smallest 25% are removed
  25. Variance
    • gives more info of the data set's variability
    • measures avg squared distance from the mean
    • often more useful to use standard deviation to express variability
  26. Standard deviation
    • square root of variance
    • interval and ratio data
    • only useful with normally distributed data
  27. Standard error of the mean
    • derived from SD
    • SEM is always smaller than SD
    • greater N = smaller SEM
    • used to calculate confidence intervals
  28. Confidence interval
    • indication of the outcome within the population
    • range of values in which the true value is included
    • ex. 95% sure that the range of values contains the true value
    • descriptive
    • help interpret clinical significance of data
  29. the width of CI measures
    • reliability of sample data
    • wide interval = less reliable
    • small interval = more reliable
  30. if the CI crosses zero with ordinal and interval data
    • possibility that there was not difference between treatment groups
    • should not be reported as statistically significant
  31. if the CI crosses 1with ratio data
    possibility that there is no difference between treatment groups
  32. advantages of CI
    • may expose manipulation
    • help in determining clinical significance
    • compliments P-value
  33. if trial shows there is no statistical significance between two groups, pay attention to
    upper end of CI
  34. if trial shows that there is a statistical difference between two groups, pay attention to
    the lower end of CI

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