Interpreting evidence 2 Flashcards
Describe confidence interval
A confidence interval gives a range of values, estimated from the sample data, which is likely to include the, unknown, population parameter (e.g. mean , RR, OR)
Describe a 95% confidence interval.
- A 95% confidence interval is a range of values within which we are 95% confident the true population mean lies (roughly speaking)
- Wider the confidence interval, less certain we are about the estimate
What does a wide confidence interval mean?
• Wider the confidence interval, less certain we are about the estimate
When is a T-test used?
T-test: allows us to statistically compare means between two groups. Used to determine whether two means are significantly different from each other
– 1 dependent continuous variable (e.g height)
– 1 independent binary categorical variable (e.g. sex)
Gives a probability (p-value) that such a difference (or a greater difference) would be found by chance, IF THE NULL HYPOTHESIS IS TRUE
• E.g compare the height of men and women, compare mean from your data with published literature, compare blood pressure readings before and after exercise
When is a chi-square-test used?
Chi-square-test: allows us to statistically compare frequencies
Allows us to statistically determine if the difference between the observed and expected numbers in each cell is significant (GIVEN THE SAMPLE SIZE)
– 1 dependent categorical variable (e.g. alternative drug types)
– 1 independent categorical variable (e.g. Deprivation category)
What is the P-value?
the probability that the observed difference (between systolic BP in my clinic compared with the previous literature) occurred by chance alone….if the Null Hypothesis is true.
What is the cut off of p?
0.05
If the probability is higher than 5% than we accept the null hypothesis
If the probability is below 5% then we reject the null hypothesis
Describe the 3 different t-tests.
– Comparison of mean with a single value (e.g. mean BP in sample vs
literature standard value)
– Comparison of means of independent samples (mean effect of statin 1 vs statin 2)
– Comparison of means of paired data ( BP before and after treatment measured in the same people)
Describe the chi-square test for independence.
association between two categorical variables (e.g: Is cholesterol status associated with gender?)
Describe the chi-square test for goodness of fit.
Tests the difference between frequencies of a single categorical variable and some hypothesised frequency
• E.g is the frequency of depression sufferers in our sample 60 men 20% of men in our sample the same as the proportion quoted in the literature
Describe correlation.
Measures the strength of relationship between two numerical variables
• e.g. Is there is a relationship between maternal and daughter age at menarche ?
• Measured by the correlation coefficient (r)
What does the correlation coefficient varying between -1 and +1 signify?
• The correlation coefficient varies between -1 and +1
r=-1 a perfect negative correlation (as one variable increases the other decreases)
r=+1, a perfect positive correlation (as one variable increases so does the other)
• For basic correlation use continuous data
Describe linear regression.
- Used to predict relationship between independent variables and an outcome (dependent) variable
- Must be a linear relationship between independent and outcome
- Is an example of a model. Want to predict the change in outcome associated with a particular change in the independent variable
- Models estimate the regression coefficient which can be thought of as the slope of the best –fitting straight line through a scatter plot of the data
- Closely related to correlation
Describe the confidence interval of the regression coefficient.
P-value for this coefficient indicates probability that the ‘true’ slope of the line is = 0 (i.e Null hypothesis is NO SLOPE).
Significant p-value (p<0.05) indicates that there is a significant slope (i.e b not equal to 0)
