10. Interpreting Evidence 1 Flashcards
Why do we need Statistics to interpret evidence?
Variability:
- Between people..
e. g differential effectiveness of treatment
e. g. Do or do not develop particular side-effect e.g. differential response to environment - Within people…
e. g. measures of blood pressure over a day e.g. strength of left and right hands
Normal versus skewed distributions
Normal distribution= Mean/median and mode at the same value in the middle (i.e. is perfectly symmetrical)
Negatively skewed= Mean
Odds ratios:
Use?
Used in case-control studies or observational studies and regression models
What defines the histogram normal distribution?
Around 68% of observations within 1SD of mean
Approx 95% of observations within 2SD of the mean
When describing location and variability…
Mean –uses _____ data but can be influenced by outliers
Median –____ influenced by outliers, but doesn’t use all data (less informative)
Mean –uses all data but can be influenced by outliers
Median –not influenced by outliers, but doesn’t use all data (less
informative)
When describing location and variability…
Mean –uses _____ data but can be influenced by outliers
Median –____ influenced by outliers, but doesn’t use all data (less informative)
Mean –uses all data but can be influenced by outliers
Median –not influenced by outliers, but doesn’t use all data (less
informative)
Risk =
Risk =Number with disease / total number at risk
ARR=
ARR= Risk 1 - Risk 2
RRR =
RRR= Risk 1/Risk2
Independent of the original prevalence.
NNT=
NNT= 1/ARR
Odds ratio (OR) =
Odds if case/ odds if control
How to calculate odds?
One type of group/ Other type
• If odds are equal in case and control group OR=
1
What is another name for baseline risk
Prevalence
When is it better to use RR instead of OR?
When events are common
What is a random sample?
In practice we can’t take measurements on every individual. We take a sample –preferably a random sample, that is representative of the population in which we are interested
Larger samples mean more…
confidence
What is standard error of the mean? (SE)
Meaning of large and small SE?
If we took repeated samples, the variability of the sample means could be measured
• A large SE indicates that there is much variability in sample
means; that many lie a long way from the population mean
• A small SE indicates there is not much variability between the sample means
Larger sample size = smaller SE
SE vs SD?
SE is always smaller than SD because there is less variability between sample means than between individual values.
What is a confidence interval?
A confidence interval gives a range of values, estimated from the sample data, which is likely to include “true” parameter
95% Confidence interval= sample parameter +/- 1.96*SE
95% Confidence interval= sample mean +/- 1.96*SE
Importance of CI?
Powerful tool for making decisions about whether observed differences are likely to be due to chance alone, or likely to be a true effect.
Null hypothesis?
(in a statistical test) the hypothesis that there is no significant difference between specified populations, any observed difference being due to sampling or experimental error.
Alternative hypothesis?
The alternative hypothesis is the hypothesis used in hypothesis testing that is contrary to the null hypothesis. It is usually taken to be that the observations are the result of a real effect (with some amount of chance variation superposed).
