
Sample size calculation for casecontrol study
To do a sample size calculation, you can use the online sample size calculator available at: http://www.math.uiowa.edu/~rlenth/Power/
Worker example
Scenario 1:
"SSyndrome (SS)" is characterized by profound irritability, disorientation and fatigue for those infected individuals. The efficacy of a vaccine (called "BG vaccine") in preventing adulthood SS remains uncertain, and a study is designed to compare the vaccination coverage rates in a group of MPH students infected with SS and a group of controls with equal sample size. Available information indicates that approximately 30% of the controls are vaccinated. The primary investigator plans to have an 80% chance of detecting an odds ratio significantly different from 1 at the 5% level of significance. If an odds ratio of 2 would be considered an important difference between the two groups, what should the sample size be included in each study group?
Assumptions
Level of significance: 0.05 Statistical power required: 0.8
This can be rearranged as
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Sample size calculations
Enter p1=0.462, p2=0.3, alpha=0.05.
Adjust sample size until reaching desired power.
Sample size in each group: 152 Total sample size: 304
Scenario 2
If number of cases is limited to 100, untick "Equal ns", set n1=100, and increase n2 until the power reaches 80%.
The required sample sizes are 100 cases and 293 controls to reach 80% power for OR of 2.
If effect sizes smaller than OR = 2 are of interest, the sample size would be larger. Use the formula shown previously to calculate p_{1}, based on particular values of p_{2} and OR.

Bar Chart
 Presents grouped data with rectangular bars with lengths proportional to the values that they represent
 Can be plotted vertically or horizontally
 Very useful for recording discrete data and show comparison

Histogram
 Represent the distribution of numerical data
 Use for continuous data, where the bins represent ranges of data

Scatter Plot
 Display values for two variables for a set of data
 Suggest various kinds of correlations between variables
 Ability to show nonlinear relationship between variables
Uncorrelated 
High positive correlated 
Low positive correlated 

Negative correlated 
Nonlinear relationship 

Box Plot
 Show descriptive statistics
 Ourliers may be plotted as individual points
 Display variation in samples of a statistical population without making any assumptions of the underlying statistical distribution.
 Spacings between the different parts of the box indicate the degree of dispersion (spread) and skewness in the data, and show outliers.
How to understand a Boxplot

Means and Error Plot
 represent of the mean and variability of data
 represent the overall distribution of the data