Biostatistics Flashcards
What are the Types of Study Data?
1- Continuous: Data is provided by some type of measurement which has unlimited options of continuous values.
2- Discrete (Categorical): Data fits into a limited number of categories. It has categories!
What are the types of Continuous Data?
1- Ratio :Has meaningful zero (Zero = none) e.g. age, height, weight, time, blood pressure
2- Interval : No meaningful zero (Zero NOT EQUAL none) e.g. temperature scales
What are the types of Discrete Data?
1- Nominal : Order does NOT matter e.g. gender, ethnicity
2- Ordinal : Order matters e.g. pain scale
What is Range?
This is the difference between the highest and lowest value.
Characteristics of a Gaussian (Normal) Distribution?
1- The mean, mode and median are the same value, and are at the center point of the curve.
2- 68% of data falls within 1SD of the mean
3- 95% of data falls within 2SD of the mean
4- 99.7% of the data falls within 3SD of the mean
What is the Null Hypothesis?
A null hypothesis (H0) states that there is NO statistically significant difference between groups.
Drug efficacy = Placebo efficacy.
The null hypothesis is what the researcher tries to disprove/reject.
What is the Alternative Hypothesis?
The alternative hypothesis states that there is a statistically significant difference between groups.
What is the Alpha Value and P-Value?
Alpha is the maximum permissible error margin that is selected by investigators. Alpha is the threshold for rejecting the null hypothesis.
The p-value is compared to the alpha value.
If the alpha is set at 0.05 and the p-value is < 0.05, the null hypothesis is rejected, and the result is statistically significant.
If the p-value >= 0.05, the study has failed to reject the null hypothesis, and the result is not statistically significant.
What is the Confidence Interval?
CI = 1 - alpha
(a is 0.05, p-value >= 0.05): Not statistically significant
(a is 0.05, p-value < 0.05): 95% probability (confidence) that the conclusion is correct; less than 5% chance it’s not.
(a is 0.05, p-value < 0.01): 99% probability (confidence) that the conclusion is correct; less than 1% chance it’s not.
(a is 0.05, p-value < 0.001): 99.9% probability (confidence) that the conclusion is correct; less than 0.1% chance it’s not.
A narrow range implies high precision, and a wide range implies poor precision.
How can we determine statistical significance with CI?
The result is statistically significant if the CI range does NOT include ZERO.
IF we are comparing Ratio Data (Relative Risk, Odds Ratio, Hazard Ratio), the result is statistically significant if the CI range does NOT include ONE. e.g. The 95% CI for the RR of moderate exacerbations (0.72-0.99) does not include 1, therefore the result is statistically significant.
What is a Type 1 Error?
False-Positives
Here the alternative hypothesis was accepted, and the null hypothesis was rejected IN ERROR.
What is a Type 2 Error?
False-Negatives
Here the null hypothesis is accepted when it should have been rejected.
The risk of a type 2 error increases if the sample size is too small. To decrease this risk, a power analysis is performed to determine the sample size needed to detect a true difference between groups.
What is the Study Power?
Power is the probability that a test will reject the null hypothesis correctly.
Power = 1 - beta
If Beta is set at 0.2, the study has 80% power (there is a 20% chance of missing a true difference and making a type 2 error)
Relative Risk (RR)
This is the ratio of risk in the exposed group (treatment) divided by the risk in the control group.
Risk = [# of subjects in group with unfavorable events] / [Total subjects in group]
RR = [Risk in treatment group] / [Risk in Control group]
RR Interpretation:
RR=1 (or 100%): No difference in risk of the outcome between the groups [Intervention had no effect]
RR>1: There is a greater risk of the outcome in the treatment group
RR<1: There is a lower risk (Reduced Risk) of the outcome in the treatment group
Relative Risk Reduction (RRR)
RRR is calculated after the RR and indicates how much the risk is reduced in the treatment group compared to the control group.
RRR = 1 - RR
*Must use the decimal version of RR
RRR Interpretation:
If the RRR is 43%, the treated patient were 43% less likely to have outcome than placebo-treated patients.