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EBM Exam I
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power is a calculation that
indicates whether or not a study can accurately detect statistically significant differences between samples when a difference exists
simply stated, power =
1 - beta
want power to be at least
80%
a priori calculation of power
number of subjects needed to meet power is figured out before the study is performed
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
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
study did not enter enough pt to meet power but difference was detected?
info we can use
study had enough participants to meet power and showed a difference between groups?
info we can use
study had enough pt to meet power and showed no difference between groups
info we canuse
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
power is mentioned but without details, no % set or number of pt required to meet power
power not met
power is claimed to be met but not reported
power not met
Three types of analysis
per protocol
intent to treat
modified intent to treat
per protocol
number of subjects completing the trial
intent to treat (ITT)
number of subjects randomized into each group
modified intent to treat
number of subjects randomized and met pre-specified criteria (ex. 8 weeks of tx)
descriptive statistics are calculated to describe characteristics of
a group
ex. patient demographics & frequency
measures of central tendency
mean
median
mode
mean
used on interval or ratio data
may be misleading on ordinal data
affected by outliers
Median
used on ordinal
non-parametric test
mode
variable that occurs most frequently
most useful with nominal data
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
Range
degree of spread
influenced by outliers
difference between largest and smallest observed
interquartile range
used for ordinal, interval and ratio data
range of values remaining when the largest and smallest 25% are removed
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
Standard deviation
square root of variance
interval and ratio data
only useful with normally distributed data
Standard error of the mean
derived from SD
SEM is always smaller than SD
greater N = smaller SEM
used to calculate confidence intervals
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
the width of CI measures
reliability of sample data
wide interval = less reliable
small interval = more reliable
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
if the CI crosses 1with ratio data
possibility that there is no difference between treatment groups
advantages of CI
may expose manipulation
help in determining clinical significance
compliments P-value
if trial shows there is no statistical significance between two groups, pay attention to
upper end of CI
if trial shows that there is a statistical difference between two groups, pay attention to
the lower end of CI
Author
Rx2013
ID
132007
Card Set
EBM Exam I
Description
biostats 2
Updated
2/4/2012, 10:38:22 PM
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